Project Budget Research Articles

RECRUITING LATINO CAREGIVERS INTO DEMENTIA-RELATED RESEARCH: NOT FOR THE FAINT OF HEART

Abstract Drawing from the theoretical model—the Micro-Meso-Macro Framework— we elucidate factors that facilitated or impeded diverse sample recruitment to a community-based caregiver intervention study with high Hispanic/Latino representation in California. Based on our multi-level analysis of recruitment meetings and community outreach tracking, we documented the following factors implicated in trial participation: 1) Micro: prior encounters with the research enterprise; educational attainment and occupational status; sense of altruism and beneficence; monetary incentivization; comfort with disclosure of private matters; starting from ground zero; gender issues; and 2) Meso/macro: assembling a proactive scientific team; incorporating a marketing perspective; leveraging logos and reputation; training trial staff and community partners; writing project budgets that incentivize diverse trial recruitment; making inroads with community partners; navigating technological challenges; and tapping into resources to alleviate barriers. Latinos were adversely affected by low exposure to research activities and technological barriers which necessitated extra supports during trial participation.

IMPACT OF LEGISLATIVE CHANGES ON THE FINANCING OF JUDICIAL ACTIVITIES IN UKRAINE

Judicial activity in Ukraine involves the examination and resolution of contentious issues related to the protection of rights, restoration of violated rights, cessation of rights violations, and application of legal influence measures. All these require appropriate resources, not just informational but also financial and material. The levels of funding depend on the judicial authority financing programs and state budget projects. In other words, changes in legislation will directly affect the volumes and timelines of funding for judicial activities. Conducting an in-depth analysis of scientific and practical literature, our goal was to identify and assess the level of impact of the latest legislative changes on the funding volumes for judicial activities in Ukraine. The object of the study is judicial activity in Ukraine. We believe that the assessment of legislative changes requires the involvement of relevant experts in law and beyond. Therefore, with the help of experts and the applied structuring technique, the weight of the impact of certain legislative changes on the amount of funding for judicial activity in Ukraine is ranked.However, determining which impact is most significant is just one of the outcomes. Additionally, measures for the judicial system's response/adaptation to the most significant changes were proposed. The limitations of the study relate to the fact that the legislative changes identified in the work are not constant and stable. In the future, there will be new changes requiring a new approach to evaluation and response.

Budget Disclosure in Crowdfunding: Information Asymmetry and Cost Transparency

Problem definition: This paper investigates how a crowdfunding campaign’s voluntary disclosure of sensitive cost information affects its funding performance on Kickstarter—a mainstream, primarily reward-based crowdfunding platform. Instead of enhancing a campaign’s marketing traits, project budget as a novel information-provision tool reminds the crowd of the behind-the-scenes operations for developing and executing a project. This resembles the radical practice of cost transparency recently observed in the retail industry and studied experimentally in the literature. We also separate the disclosure effect on reward seeking versus altruistic pledges and examine how it varies with the structure of the cost items (fixed versus variable costs). Methodology/results: Our data collection follows Kickstarter’s rollout of the Project Budget tool in 2019. The project-level raw data are preprocessed via coarsened exact matching to match projects with and without budgets. We show that the main channel through which budget provision improves funding performance is via attracting additional funding, not by cannibalizing competing projects. Because of the voluntary nature of budget provision, we address the resulting endogeneity issue using peer average-style instruments. Budget provision on average increases funding performance by over 100%, which is more effective than many information-provision tools studied. Interestingly, this funding improvement comes from an increased number of backers (width), not from a higher pledge per backer (depth), and from a considerably higher number of altruistic pledges, not from more reward-seeking pledges. Further, a higher fixed-cost (over total cost) ratio, which is indicative of a higher profit margin, significantly reduces the benefit but does not make disclosure backfire. Managerial implications: Showing the costs to customers can be highly effective in business settings where trust between stakeholders is critical, which implies a promising generalization to donation-based crowdfunding. Our results can also be used to guide a sequential rollout of the Project Budget feature across campaign categories and promote adoption rates. Funding: X. Tong was supported by funding from the Department of Operations and the Research School of the Faculty of Economics and Business at the University of Groningen [Projects 147215070 and 147120310]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0374 .

Optimizing Software Cost Estimation: A Hybrid Approach Integrating Soft Computing Techniques for Enhanced Accuracy and Efficiency

In software engineering, software cost estimate is a necessary process directly affecting project deadlines, budget planning, and resource allocation. Conventional estimating methods could overlook the inherent complexity and uncertainty of software development, therefore causing mistakes and maybe project failures. To optimise software cost estimation and so address these challenges, this work proposes a hybrid framework incorporating fuzzy logic, artificial neural networks (ANN), and genetic algorithms (GA). Although fuzzy logic models imprecise and ambiguous information to control uncertainty, ANN is employed for its ability to learn and generalise patterns from past data. GA guarantees accurate and effective assessment of the process by strengthening already used techniques with strong optimising characteristics. Combining these techniques makes use of their respective benefits to generate a synergistic plan beyond more traditional methods. The proposed framework is investigated using industry-standard datasets exhibiting appreciable increases in prediction accuracy, computational efficiency, and flexibility to varied project situations. Comparatively, for complex and large-scale projects the hybrid approach not only reduces estimating errors but also enhances scalability and dependability. Additionally included in the paper is a case application for a practical project, therefore stressing the relevant usefulness of the framework. By addressing the limitations of present approaches, this work reduces the gap between theoretical breakthroughs in soft computing and their pragmatic use in software engineering. stressing the need of applying contemporary computing techniques to solve evolving challenges in cost estimation, the outcomes provide useful information for scholars and business practitioners. At the end of this work is explored the possibility of new machine learning models and the investigation of domain-specific customisations to increase the applicability of the framework.

Quantitative risk assessment: methodology and application in an automaker body-in-white production line project

Purpose: this research aims to introduce a novel methodology, termed Quantitative Risk Assessment for body-in-white projects, to forecast the expected project completion time and total project cost. This methodology is demonstrated through application to a real project within an automotive manufacturer in Brazil. Theoretical framework: the study employs established risk analysis methods (e.g., program evaluation and review technique, preliminary hazard analysis, Gaussian curve, Monte Carlo simulation) alongside project management tools for problem characterization (e.g., project requirements, assumptions, work breakdown structure). Methodology/Approach: the methodology presented in this paper follows a sequence of methods that: (i) identify the hazards; (ii) evaluate the probability of risks associated with each project task; (iii) assess their consequences and impact on project costs; and, finally, (iv) quantify the risks to predict a probability spectrum for the project’s total cost. This allows estimating an emergency reserve and categorizing the risk level to inform stakeholders. Findings: The paper reveals that, among the 66 identified hazards, there is a 37% probability of the project duration exceeding 200 days, and the project has been categorized as high risk (i.e., more than a 20% probability that additional costs will exceed 20% of the estimated project budget). Research, practical & social implications: this study enables organizations to forecast the potential impacts of risks on project schedules and costs through comprehensive risk assessments, providing valuable input for project risk management. Originality/ Value: the study’s value lies in the originality of its risk assessment methodology applied to automakers’ body-in-white projects. Keywords: Automaker. Body-in-White. Monte Carlo Simulation. Probabilistic modeling. Quantitative risk assessment.

Optimizing Cost Efficiency through Cost Control in Construction Projects: A Review

This study explores various methodologies and factors influencing budget performance across different sectors, particularly in construction and public budgeting. Construction projects are inherently complex and prone to cost overruns, making cost control a critical aspect of project management. This study investigates the impact of cost control on cost efficiency in construction projects. A neural network model was utilized to identify key management factors affecting project budget performance, focusing on critical aspects such as project manager experience, team turnover, and budget updates. Several monitoring techniques for cost and performance deviations, including Activity-Based Ratios, were also analyzed, revealing their varying effectiveness. In the public sector, performance-based budgeting systems were discussed, with an emphasis on integrating planning and performance metrics for more informed decision-making. Challenges in implementing such systems were highlighted, particularly regarding political and organizational barriers. In construction, various approaches were examined, including cost estimation frameworks and performance-based budgeting tools. The research underlined the importance of accurate budgeting and cost control measures in both construction projects and public administration, suggesting that strategic adjustments, better forecasting, and active stakeholder participation could improve overall budget performance. This research paper presents a comparative analysis of various process-based cost control models utilized in construction projects. The objective is to evaluate each model’s effectiveness, advantages, and limitations to provide insights for project managers in selecting the most suitable approach for their specific project needs. Key Words: Cost Efficiency, Cost Control, Construction, Projects

Fuzzy repetitive scheduling for construction projects considering risk preferences and time-cost tradeoffs

PurposeThe purpose of this study is to develop a novel approach that addresses time-cost tradeoffs in repetitive construction projects while considering the uncertainty in activity durations and the risk preferences of planners.Design/methodology/approachOur study involves work in three aspects. Firstly, it employs triangular fuzzy numbers to represent activity durations in different units, which facilitates the management of scenarios characterized by limited historical data or the presence of ambiguous information. Secondly, it introduces a fuzzy chance-constrained programming model, which is aimed at minimizing the project budget while ensuring that the risks associated with cost overruns and schedule delays are confined to specified limits. Thirdly, it advances an enhanced genetic algorithm, integrating an electromagnetism-like mechanism and a scheduling repair process, to improve the efficiency and effectiveness of the optimization process.FindingsA real-life street renovation project was analyzed to demonstrate the applicability of the proposed algorithm. The analysis explored three common types of risk preferences: risk-averse, risk-neutral and risk-loving. The results indicate that the proposed algorithm surpasses existing fuzzy repetitive scheduling methods in terms of risk management. It effectively generates schedules that align with the risk preferences of planners and provides worst-case estimates of project performance.Originality/valueThis research makes a significant contribution to the field by developing a fuzzy chance-constrained programming model and an associated optimization algorithm that is specifically designed for time-cost tradeoffs in repetitive construction projects. A key distinction is that this study considers the risk preferences of planners, which sets it apart from previously developed models. As a result, it provides a practical approach for effective risk management.

Analyzing Bid and Indicative Prices in Historic Building Reconstructions in the Czech Republic

Abstract Valuing the reconstruction of historic buildings is a complex and challenging task due to the unique nature of these structures and the uncertainties involved in estimating the scope of work. This study aimed to bridge the gap between traditional construction practices and modern economic frameworks by developing a comprehensive methodology for the valuation of construction works on historic buildings. Focusing on the Czech Republic, the study analysed the tender budgets of 21 reconstruction projects to be carried out between 2020 and 2023. The analysis compared tender prices with standardised indicative prices to identify significant discrepancies and the reasons for them. The proposed methodology integrated market-based price analysis and traditional pricing tools, providing a robust framework for accurate cost estimation. This approach not only ensured the preservation of the cultural value of historic buildings, but also provided a practical, financially sound strategy for their restoration. The findings of this study provide valuable insights for stakeholders involved in the pricing and budgeting of restoration projects, helping to refine cost estimation methodologies and improve the efficiency and accuracy of budgeting processes.

Analysis of Volume Calculations for Clay Mining Excavation Plans Using The Surface to Surface Method

Abstract Calculating the volume of excavation is generally a large and complex problem for a project in an industry. This is because the accuracy of the volume calculation affects the project budget for the project provider. Calculating the excavation volume is important aspect of mine planning since it serves as a guide for hitting production goals in terms of both profit and technical success. The method commonly used in calculating excavation volume is surface to surface. To overcome this problem, a method or technique is needed to calculate the excavation volume that can provide accurate calculation results. the surface-to-surface approach will be used to optimize volume calculations. Additionally, the accuracy of excavation volume calculations based on ASTM (American Society for Testing and Material) tolerances. Analysis is carried out by calculating the smallest percentage value. In this way, excavation volume results will be obtained that are close to the reference value based on ASTM tolerances. The aim of this research is to determine the optimal results of surface-to-surface method volume calculations from the most accurate contour intervals. The volume calculation results that are closest to the reference of 999,922.91 tonnes have a percentage value of 0.01% with a volume difference to the forecast study of 77.09 tonnes. To obtain accurate volume calculations, a contour interval of 1 meter is better than several other contour intervals. This research can become new alternative in volume calculations to support SDGs activities, especially in the resource use efficiency to achieve a sustainable industrialisation.

An Analysis of the Performance of Citizen-led Projects: Focusing on Suwon City’s Participatory Budgeting and Community Renaissance Projects

An Analysis of the Performance of Citizen-led Projects: Focusing on Suwon City’s Participatory Budgeting and Community Renaissance Projects

Cost Estimation for the Operation and Maintenance of Automated Monitoring and Early-Warning Equipment for Geological Hazards

Geological hazards impede regional economy sustainability. To limit their destructive impacts on human life and property, the Chinese government has independently developed automated monitoring and early-warning equipment, which has been deployed in over 250,000 locations nationwide, yielding effective early warnings. The smooth operation of this equipment necessitates substantial human, material, and financial resources for its maintenance. To allocate funds rationally, the Ministry of Finance of China has mandated the urgent establishment of budget standards for the operation and maintenance of automated monitoring and early-warning systems for geological hazards. Addressing the research gap in this area, this study meticulously develops a cost model, subcategorizing operating costs, maintenance costs, and management costs. Addressing the intricate issue of maintenance expenditures, this study ingeniously breaks down routine operations and urgent repairs stipulated in technical standards into personnel, materials, and vehicular needs for each equipment type. Considering the total manpower involved in equipment maintenance, the per-unit maintenance cost is determined. This method allocates costs to individual pieces of equipment, thereby sidestepping the quantification hurdle created by varying types and quantities of monitoring equipment at each monitoring site due to various geological disaster types and magnitudes, and technical personnel’s maintenance responsibility for multiple equipment types in a single operation. Finally, incorporating regional adjustment coefficients, we have formulated theoretical costs for the operation and maintenance of automated monitoring and early-warning equipment for geological hazards. By contrasting theoretical costs with actual project budgets, the error margin is within 2%. Following nationwide consultation, these theoretical costs have been officially endorsed as the budget standard. These standards will lay the groundwork for project budgeting and review, facilitate efficient fund utilization, and ensure the financial sustainability of monitoring and warning systems for geological hazards. Concurrently, this paper bridges the global lack in budget norms for the operation and upkeep of automated geological disaster monitoring systems. The cost calculation model introduced serves as a pivotal reference globally for the evaluation of analogous system’s operations and maintenance expenses.

PROJETO DE INFRAESTRUTURA DE PAVIMENTAÇÃO ASFÁLTICA, DRENAGEM PLUVIAL E ORÇAMENTO DO NOVO LOTEAMENTO PRÓXIMO AO BAIRRO VALE DO OURO EM TOCANTINS-MG

This article presents the infrastructure project for the development of a new urban subdivision near the Vale do Ouro neighborhood in the municipality of Tocantins, MG. The proposal encompasses the construction of asphalt paving for both main and secondary roads, the implementation of a stormwater drainage system designed to prevent flooding, and the preparation of a detailed budget to optimize the financial resources applied to the project. The pavement and drainage infrastructure is essential to ensure road durability and the safety of future residents, protecting residential areas from issues such as erosion, flooding, and soil degradation. This project thus aims to meet urbanization demands and provide a higher quality of life, contributing to the sustainable and orderly development of Tocantins. To achieve this, technical studies, field surveys, and budget projections have been conducted to enable a complete and functional project, aligned with modern standards for urban infrastructure safety and comfort.

Review on assessing climate-change-induced risks to run-of-river hydropower infrastructure in Nepal

Abstract. Nepal annually invests millions of dollars in hydropower development, with a substantial portion of these funds allocated to civil infrastructure. Climate change, which impacts geological and hydrological conditions, poses a threat to civil components throughout hydropower project construction and operation. This causes budget overruns, project delays, and adverse consequences for society and the environment, ultimately resulting in multimillion-dollar losses. The identification of risk factors and their underlying causes, stemming from the impacts of climate change, constitutes a fundamental aspect of this study. This critical analysis primarily draws upon extensive literature reviews to pinpoint these factors (risk factors arising from climate change), emphasizing their economic and human impacts. This paper highlights the risks to run-of-river hydropower infrastructures in Nepal. The findings of the study can be used to develop and implement adaptation strategies to mitigate the risks posed by climate change to Nepal's vital hydropower sector.

Louveira Digital City

The Louveira Digital City is a municipal information network designed to promote digital appications development, offering e-government services in areas such as health, education, social assistance, safety, and public works. The project began as an academic initiative focused on Louveira's Information Highway, which was presented to the City Council in August 2010. It outlines the key components of the information highway, including the optical backbone architecture, feasibility study, radio link specifications, logical network design, equipment specifications, and project budget. This digital infrastructure enables all residents to access various communication services and applications, such as data, video, and voice traffic. The network is comprised of radio and fiber optic links, designed to benefit various areas of public administration, including health, safety, education, and planning. Additionally, it aims to enhance public access to information, culture, education, and leisure, laying the groundwork for a smart city. This project showcases the implementation of the information highway in Louveira, highlighting how academic institutions can contribute to the economic, social, and technological development of society and serving as a model for similar initiatives.

Assessing Project Resilience Through Reference Class Forecasting and Radial Basis Function Neural Network

A project needs to be able to anticipate potential threats, respond effectively to adverse events, and adapt to environmental changes. This overall capability is known as project resilience. In order to make efficient project decisions when the project is subjected to disruption, such as adjusting the project budget, reformulating the work plan, and rationalizing the allocation of resources, it is necessary to quantitatively understand the level of project resilience. Therefore, this paper develops a novel approach for forecasting project performance, illustrating the changes in performance levels during the disruption and recovery phases of a project and thus quantitatively assessing project resilience. While there are several methods for assessing project resilience in existing research, the majority of assessment approaches originate from within projects and are highly subjective, which makes it difficult to objectively reflect the level of project resilience. Moreover, the availability of project samples is limited, which makes it difficult to forecast the level of project performance. In view of the fact that the Reference Class Forecasting (RCF) technique avoids subjectivity and the Radial Basis Function (RBF) neural network is known to be better at forecasting small sample datasets, this paper therefore combines the RCF technique and the RBF neural network to construct a model that forecasts the project performance of the current project after experiencing a disruption, further assessing the level of the project resilience. Specifically, this paper first presents a conceptual model of project resilience assessment; subsequently, an RBF neural network model that takes into account project budget, duration, risk level of disruption, and performance before disruption based on the RCF technique is developed to forecast project performance after experiencing disruption; and finally, the level of project resilience is assessed through calculating the ratio of recovery to loss of project performance. The model is trained and validated using 64 completed construction projects with disruptions as the datasets. The results show that the average relative errors between the forecast results of schedule performance index (SPI) and the real values are less than 5%, and the R2 of the training set and the testing set is 0.991 and 0.964, respectively, and the discrepancy between the forecasted and real values of project resilience is less than 10%. These illustrate that the model performs well and is feasible for quantifying the level of project resilience, clarifying its impact on project disruption and recovery situations, and facilitating the decision-makers of the project to make reasonable decisions.

How to monitor local objectives for urban climate change adaptation? Insights from quantitative content analysis of selected participatory budgets in the upper Silesian-Zagłębie Metropolis

Subsequent analyses of participatory budgeting in Poland emphasise the popularity of environmental issues such as greenery, air quality, and sustainable transport, which should also support objectives in urban climate change adaptation (UCCA). An increasing number of adaptation projects within local standards or ‘green’ civic budgets are often listed among the indicators in urban adaptation plans for Polish cities. However, available research studies and urban evaluation reports show that monitoring participatory budgets poses a methodological challenge. Therefore, the aim of the article is twofold. First, it proposes a method of identifying overlaps of urban climate change adaptation objectives with descriptions of projects submitted to local participatory budgets of the Upper Silesian-Zagłębie Metropolis. For this purpose, a dictionary-based text analysis of project descriptions was performed and critically examined. The second aim was to identify trends in urban climate change adaptation objectives. Thus, the quantitative distribution of coded descriptions was evaluated to investigate how subsequent types of participatory budgets (editions, green vs. standard, implemented vs. non-implemented) differed. The results demonstrate that the available database of participatory budget projects is a rich source of information on local preferences towards issues related to UCCA. To strengthen the objectives of urban climate change adaptation, city administrations can consider additional tools, such as UCCA-related tips/inspiration and targeted calls for projects, as well as supplementing participatory budgets with other deliberative methods. However, collecting precise and calculable data on this topic based on participatory budget databases requires both methodological adjustments and careful validation.

Development and application of ex-ante performance evaluation framework for health projects in China

China National Health Commission issued an implementation plan for budget performance management in health projects in April 2021, which emphasizes all health projects must be evaluated in advance prior to implementation. The study aims to develop an ex-ante performance evaluation framework for health projects and formulate a self-assessment report template. The study also attempts to gain insights into the ex-ante performance of health projects in China, identify issues and explore the factors that influence the ex-ante performance of health projects and make suggestions about improvement strategies. The framework was established by using a framework development methodology. To develop the framework, the findings from existing research were pooled and organized to create indicators and key points. The preliminary ex-ante performance evaluation framework was refined, validated and tested by the experts. Weight analysis was conducted by using the Analytic Hierarchy Process. Then the indicator system has been transformed into a project ex-ante performance self-assessment report template. Samples of 698 municipal health projects in China from 2021 to 2022 were analyzed. We invited experts to complete the scoring task by using our ex-ante performance evaluation framework. The ex-ante performance evaluation framework primarily examines five aspects, the necessity of the project, economy of input, rationality of performance indicators, feasibility of implementation plans, and compliance of financing. The overall ex-ante performance evaluation score for the sample projects was (91.19 ± 8.02). The sub-scores for necessity of project were (14.74 ± 1.85), economy of input was (34.45 ± 2.43), reasonableness of performance indicators was (8.27 ± 2.28), feasibility of implementation plan was (23.99 ± 3.84), and compliance of financing was (9.75 ± 1.47). Factors such as whether it was an epidemic prevention and control project, the project budget, project content, project objective, and project implementation organization were all influencing the ex-ante performance of health projects (P < 0.05). We have developed a ex-ante performance evaluation framework for health projects and established a project ex-ante performance self-assessment report template. They can offer a sufficient reference for project process management. Project implementation organization should elevate the awareness and proficiency of project managers regarding budget performance management. Government should improve the ability of ex-ante performance evaluation, and eliminate ineffective projects through ex-ante performance evaluation.

Risk assessment through feature, event, and process for repurposing suspended oil and gas wells for geothermal purposes

Many countries have set the goal of net zero carbon emission and are diverting their energy source towards renewables. In that respect, geothermal energy is a continuous renewable energy source that is not affected by any metrological conditions. However, geothermal energy is not used to its full potential, and at present, less than 1 % of renewable energy is produced by geothermal sources. One of the biggest reasons that hinder its adoption is the cost of drilling and completion associated with the geothermal well, which almost takes 50 % of the project budget. Therefore, it is important that, where possible (with conducive geothermal conditions), conventional oil and gas wells that are old or temporarily suspended should be retrofitted into geothermal wells. In this way, the initial cost of the geothermal project can be reduced, which is mainly due to the drilling operations. However, before repurposing old retired wells, conducting a proper risk assessment is important to avoid any well integrity issues in the long run. Therefore, this paper presents a concept of accessing the risk using Feature, Event, and Process (FEP) that have been integrated with the interaction matrix, incident potential matrix (IPM), and cause-effect plot diagram. This risk assessment technique identifies the well components that might be susceptible to failure, and remedial work should be conducted on such elements. However, geothermal wells have no specific FEPs; hence, the FEPs from CCS wells have been used, which have their limitation when used for geothermal systems. Nonetheless, to show the feasibility of this approach in assessing the risk, two case studies of the fictitious tubingless geothermal well are presented in this paper.

Robustness of prefabricated construction supply chain network against underload cascading failure

A prefabricated construction supply chain(PCSC) is a complex network with high interdependency between entities. After disturbance, it is prone to cascading failure, leading to project delays or budget overruns. Therefore, it is necessary to model a robust network against cascading failure to achieve a sustainable prefabricated construction system. This study explores the functional robustness of a prefabricated construction supply chain network (PCSCN) against underload cascading failure. First, the PCSCN is constructed as a three-echelon supply chain network based on complex network theory, which can characterize the general characteristics of PCSC and provide the network foundation for the subsequent numerical simulation research. Then, a more realistic underload cascading failure model that adds the new element of substitute nodes is established to describe load loss propagation in the PCSCN. Finally, the Order Fulfillment Rate(OFR) is used as the robustness index to quantify network robustness from a functional perspective. The numerical simulation results indicate that in the PCSCN, the larger the initial load is, the more important the node, and component manufacturers are more important than building material suppliers. In addition, the node capacity upper bound parameter α has a positive relationship with robustness, the failure coefficient β has a negative relationship, and the edge weight adjustment coefficient θ has no significant impact on robustness. This research can provide guidance for developing cascade control and defense strategies in PCSCN risk management.

Strategies used for knowledge dissemination and outreach in a renewable energy project

This work describes the actions carried out by participants of the Mexican Center for Innovation in Ocean Energy project (CEMIE-Océano) to disseminate their advances and results, to the general public and to the scientific community. The project was set up to assess the energy potential in Mexican coastal areas related to waves, tides and currents, and salinity and thermal gradients, and also to investigate their expected environmental and social impacts. The main actions by the CEMIE-Océano dissemination, outreach and press area, 2017 - 2023, were the design, construction and administration of the project website, the regular publication of activities and major achievements on social media via Facebook and Twitter, and the editing of 28 scientific books and nine editions of a biannual newsletter. Eight work meetings, three conferences and a range of science dissemination seminars were also organized. With the strategies presented in this work, for a value close to 3% of the total project budget, the participation of all the collaborators was achieved. In addition, the CEMIE-Océano project is widely recognised within the community of scientists from Mexico and Latin America, and others interested in renewable energies and energy transition issues. Keywords: CEMIE-Oceano project, ocean energy, dissemination, outreach.