Cost Estimates Research Articles

Development of Agribusiness in Tiwi, Albay

This study determined the status of agribusiness in Tiwi, Albay, as basis for the development of business plan. Specifically, it sought to answer the following sub- problems: 1) What are the areas of agribusiness in the Municipality of Tiwi, Albay?; 2) What are the status of agribusiness along; crop production, animal production, aquaculture production, and agri-support services and manufacturing?; 3) What are the contributions of the above areas in the agribusiness in Tiwi, Albay?; 4) What are the problems encountered in agribusiness?; and 5) What business plan may be proposed to address the problems encountered in agribusiness? The study involved presenting the agribusiness sectors contributions through tables and charts, emphasizing their economic impact and community significance. It addressed challenges by organizing issues like infrastructure or market access, supported by relevant data or case studies. It proposed a comprehensive business plan targeting specific problems with detailed strategies, cost estimates, and potential outcomes. Descriptive surveys are crucial in agribusiness research, providing detailed insights into agricultural practices and factors affecting productivity within a specific population. These surveys utilize statistical tools such as frequency percentage and weighted mean to accurately depict response distribution and measure the significance of variables. Synthesizing findings and ensuring proper citation and definition of terms in research helps draw meaningful conclusions and contribute to a broader understanding of agribusiness practices in the region. Incorporating literature demands a structured approach, starting with an introduction highlighting the topic's significance, organizing sources thematically or chronologically, and synthesizing findings while ensuring proper citation and defining terms for clarity. Descriptive surveys in agribusiness employed tools like frequency percentage to depict response distribution and weighted mean to gauge variable significance, offering precise insights into agricultural practices and factors affecting productivity within the surveyed population.

Waiting for surgery after hip fracture-Health and/or economic risk?

Waiting for surgery is a disconcerting experience. It can have a negative impact on patients' outcomes and length of stay (LOS) as driver for treatment costs. Process-optimisation may be a strategy to improve quality and cost-efficacy. The study investigates the correlation between waiting for hip fracture surgery and patient characteristics, organisational variables, outcomes, LOS, and the distribution of waiting times and LOS over time, including cost estimates. Thereby the study aims to identify the potential for organisational improvements with respect to managing the waiting time. Ten-year routine health data (patient characteristics and follow-up information) and process-indicators that is, waiting time and LOS from a Swiss trauma-centre were analysed retrospectively. Cost-estimates were calculated based on Swiss diagnosis related groups and daily costs to evaluate hospital revenues. In total, 2572 patients aged ≥60years with low-energy hip fractures were included. Waiting times >48h were associated with sub-optimal outcomes. Over the years long waiting times decreased. This reduction was not reflected by a reduction in LOS which remained stable around 10days, primarily driven by late discharge to in-patient rehabilitation. Reimbursement persisted at an average revenue in the low 4-5-digit range, depending on implant costs. While there has been a reduction of waiting times, this has not translated into a reduction of LOS or potential savings in health care costs, due to the various dependencies along the patient journey. Managing waiting times may be an area for improvement, increasing cost-efficacy, especially since long waiting times are still associated with inferior outcomes and LOS.

A tree-based approach to identify indispensable foods in minimum-cost food baskets.

Optimization techniques, such as linear programming, can be used to estimate the minimum cost of a nutrient-adequate food basket, to determine if individuals or households can afford nutritious diets. These cost estimates typically account for seasonal fluctuations but often overlook significant disruptions in the availability of affordable nutritious food that can severely impact food and nutrition security. This paper proposes a tree-based method, the binary search tree, to assess the resilience of the cost estimate of the minimum-cost food basket. In particular, this method aims to identify indispensable foods in these baskets - those whose unavailability would lead to a substantial cost increase. The binary search tree operates by iteratively excluding essential food items while ensuring the construction of minimum-cost nutritious baskets. It considers all relevant combinations of foods up to a specified size and avoids unnecessary optimizations, thereby saving computation time. We describe how the resulting tree can be evaluated and condensed to capture only the necessary information for decision makers. The construction and evaluation of the binary search tree are independent of the (dietary) restrictions or type of optimization model (i.e., linear, non-linear or integer) included. In general, the binary search tree can identify all (combinations of) foods whose exclusion leads to a significant cost increase of a nutritious food basket. Furthermore, it can detect possible substitute effects between foods and identify key limiting nutrients. A case study is presented in which the binary search tree is applied to data from Ebonyi, Nigeria, modeled using linear programming. We report all combinations of up to five foods that, when unavailable, can impact food and nutrition security in Ebonyi. The BST can provide insights into local food and nutrition security when facing drastic disruptions in access to nutritious foods by identifying indispensable foods. Its results can be used to inform and design interventions in the context of humanitarian operations.

Improvement of the UCP method for estimating labor costs in the implementation of IT-projects

An important stage of planning in the implementation of IT-projects is the assessment of the complexity of software development. An accurate estimate of labor costs at the early stage of the project life cycle significantly affects the allocation of resources, time planning and budget costs. Therefore, regardless of the large number of methods used to estimate labor costs during the implementation of an IT-project, the task of increasing the accuracy of this predictive estimate is relevant. The paper examines in detail the possibilities of using the well-known method for estimating labor costs Use Case Points (UCP), which is based on the use of use cases. It belongs to algorithmic methods, which makes it quite reliable and predictable in use. It also allows you to take into account the functional requirements for the system, which is especially useful in the early stages of project implementation. In addition, UCP is not tied to specific technologies or programming languages, which indicates its universality and flexibility. The purpose of the study is to improve the UCP method of estimating labor costs necessary for the successful implementation of an IT-project, which will allow taking into account interval estimates of technical complexity factors and external factors that affect the estimation of the amount of software and, accordingly, the estimation of the project's labor intensity. To experimentally verify the operability and efficiency of the proposed modified UCP method, a dataset containing information on 71 real projects was used. The results of computer modeling and comparative analysis of the accuracy of estimates of labor costs for the implementation of the project obtained using the proposed and original UCP methods are given. The results of the experiments showed that the proposed modification of the UCP method allows obtaining more accurate predictive estimates of labor costs in the implementation of IT-projects, which can significantly affect the efficiency of planning and project management processes.

State of HIV costing in Latin America and the Caribbean: a systematic literature review.

To summarize available data on unit costs for human immunodeficiency virus (HIV) testing, prevention, and care interventions in Latin America and the Caribbean. We conducted a systematic literature review of costing studies published between 2012 and 2024, and selected those reporting empirically measured costing data. The available data were categorized according to predefined intervention categories and compared by time and place. We also explored variations in unit costs by intervention type. Of 1 746 studies identified, 22 met the inclusion criteria, which provided 103 unique unit cost estimates from nine countries. About 50% of the included studies were published between 2019 and 2021. Antiretroviral therapy services had the most cost data available (39% of unit costs), followed by inpatient care (27%) and HIV testing (24%). Considerable cost variations were observed both within and between interventions. Our analysis underscores the need for accurate and reliable cost data to support HIV budgeting and decision-making efforts. We identified several gaps in the availability of cost data and emphasize the importance of presenting results more effectively by incorporating key contextual variables. Given the challenges of shrinking budgets and sustainability risks, robust evidence is indispensable to inform priority setting and budget allocation for HIV services.

A cost comparison of GLP-1 receptor agonists and bariatric surgery: what is the break even point?

With the prevalence of obesity rising in the US, medical management is of increasing importance. Two popular options for the treatment of obesity are bariatric surgery (e.g. sleeve gastrectomy and Roux-en-Y gastric bypass) and the increasingly popular GLP-1 Receptor Agonists (GLP-1s). This study examines the initial and long-term costs of GLP-1s compared to bariatric surgery. We compared average 2023 national retail prices for GLP-1s to surgical cost estimates from 2015 adjusted for inflation. We then plotted the cumulative medication cost over time against the flat cost of each surgery, thus calculating "break-even points" (when medication costs equal surgery costs). The findings revealed a crucial insight, for some GLP-1s like Saxenda and Wegovy, the high cost of ongoing use surpasses the cost of RYGB in less than a year and sleeve gastrectomy within nine months. Even the most affordable option, Byetta, becomes costlier than surgery after around 1.5years. This highlights the importance of looking beyond the initial financial investment when considering cost-effectiveness. Additionally, while not directly assessed, this study acknowledges that GLP-1s take time to reach full effectiveness, potentially delaying weight loss while accumulating costs. Concerns also exist about weight regain after discontinuing the medication. This study is limited by the real-world variation for individual treatment costs (e.g. insurance), a limited evaluation of long-term costs associated with either treatment modality and their co-morbidities, and the reality of patient preference providing subjective value to either modality. Overall, the study offers insights into the financial trade-offs between GLP-1s and bariatric surgery.

Dynamic soaring decouples dynamic body acceleration and energetics in albatrosses.

Estimates of movement costs are essential for understanding energetic and life-history trade-offs. Although overall dynamic body acceleration (ODBA) derived from accelerometer data is widely used as a proxy for energy expenditure (EE) in free-ranging animals, its utility has not been tested in species that predominately use body rotations or exploit environmental energy for movement. We tested a suite of sensor-derived movement metrics as proxies for EE in two species of albatrosses, which routinely use dynamic soaring to extract energy from the wind to reduce movement costs. Birds were fitted with a combined heart-rate, accelerometer, magnetometer and GPS logger, and relationships between movement metrics and heart rate-derived V̇O2, an indirect measure of EE, were analyzed during different flight and activity modes. When birds were exclusively soaring, a metric derived from angular velocity on the yaw axis provided a useful proxy of EE. Thus, body rotations involved in dynamic soaring have clear energetic costs, albeit considerably lower than those of the muscle contractions required for flapping flight. We found that ODBA was not a useful proxy for EE in albatrosses when birds were exclusively soaring. As albatrosses spend much of their foraging trips soaring, ODBA alone was a poor predictor of EE in albatrosses. Despite the lower percentage of time flapping, the number of flaps was a useful metric when comparing EE across foraging trips. Our findings highlight that alternative metrics, beyond ODBA, may be required to estimate energy expenditure from inertial sensors in animals whose movements involve extensive body rotations.

Food Insecurity Cost Estimates for El Paso, Texas

Food insecurity is a fairly pervasive problem throughout the United States that is especially burdensome for low-income regions. While the latter is generally recognized, there have been very few efforts to quantify the dollar costs of food insecurity, especially at the regional level. This study attempts to do so for El Paso County, Texas. This is achieved by first adjusting for inflation cost estimates in a prior national level study. Regional differences with respect to the nation are then utilized to calculate comparable costs for El Paso. Results indicate that the economic damage wrought by food insecurity in El Paso during 2023 exceeded $745 million. That represents nearly 2 percent of total personal income in the county for that year.

System-based ship design of a deep-sea mining vessel

ABSTRACT This paper applies the system-based ship design (SBSD) method to the conceptual design of a deep-sea mining vessel. The anticipated mine site is situated on the Norwegian extended continental shelf, where three production scenarios are assessed. The design process is documented, including a problem statement, mission description, functions, space requirements of various sub-systems, stability calculations, and preliminary cost estimates. A combination of data from existing technologies and estimates is used to set the relevant parameters, and the applicability of SBSD in the conceptual design of novel vessels is discussed. We find that when data is lacking in conceptual ship design, inspiration can be found from similar systems in established maritime industries, such as the offshore oil and gas industry.

393 The role of on-animal sensors in understanding feed intake, behavior, and performance of grazing livestock

Abstract Intake by grazing animals is difficult to reliably measure in the field, particularly in more diverse grazing systems where pastures vary greatly across time and space in resource availability, which in turn leads to greater variation in animal time budgets and intake patterns. Advances in remote livestock monitoring (e.g., on-animal sensors, walk -over-weighing), and advanced analytics such as machine learning algorithms can contribute to the development of robust, adaptable tools for better understanding of animal performance and behavior in grazing systems. Many existing tools for predicting livestock production require estimates of feed intake, and while estimates based on forage sward characteristics have been developed and used for temperate, relatively homogenous pastures, they are less well defined for more diverse rangelands. These diverse pastures are more difficult to characterize due to their greater variation in quantity and quality; consequently, animal selectivity is greater in more variable pastures. However, such feedback loops between pasture diversity and animal behavior may not yet be adequately represented in biophysical models. On-animal sensors such as accelerometers and GPS devices can be used to develop new ways of assessing relative intake by providing accurate estimates of animal location and behavior profiles, such as the use of machine learning algorithms to detect how much time is spent grazing, walking, ruminating, or resting. Measurements of animal behavior could then be combined with other animal-based methods such as walk-over-weighing and fecal NIR to improve estimates of intake and production for a wide range of extensive grazing environments. Sensor-derived measurements of animal movement could also be used to improve estimates of the energetic costs of grazing, thereby improving estimates of energy available for growth. As an example, data on recent activity and paddock use from on-animal sensors could be entered into a model to estimate current feeding requirements, then combined with weather and pasture quality forecasts. The ensuing baseline could then be used to explore the potential variability of these projections and generate a range for possible expected performance over the next month or season. This approach could be repeated over time, and animal performance and behavior measures used to update model estimates and improve forward projections. These methods could also be used in conjunction with estimates of animal energy requirements to provide real-time prediction of relative feed intake, which would provide a step-change in modelling livestock production in extensive grazing systems. For these approaches to be successful, additional calibration data are needed across a wide variety of environments and species, and the tools must be cost-effective to implement. In summary, on-animal measurements provide an adaptable, data-driven approach that could be integrated with existing tools to improve our understanding of feed intake, behavior, and performance of grazing animals.

Towards a social cost of carbon with national characteristics

The majority of estimates of the social cost of carbon use preference parameters calibrated to data for North America and Europe. We here use statistically representative data for attitudes to time and risk across the world. The social cost of carbon is substantially higher in the global north than in the south. The difference is more pronounced if we count people rather than countries.

Cost of a Healthy Diet: A Population-Representative Comparison of 3 Diet Cost Methods in Canada

BackgroundDifferent food price sources and dietary assessment tools may impact the estimation of diet costs and hamper our understanding of the relationship between diet costs and dietary intakes. ObjectivesWe aimed to investigate the effect of 3 diet cost derivation methods, with increasing numbers of food prices and geographic specificity, holding consistent the dietary assessment tool, on the estimation of diet costs overall and by food group. MethodsWe matched 24-h dietary recall data from the 2015 Canadian Community Health Survey-Nutrition (CCHS-N) to food price data from 3 Canadian Consumer Price Index (CPI) food price lists; national short list, national long list, and provincial long list. We compared the daily ($/day) and energy-adjusted ($/2000 kcal) diet costs overall and by food groups for the overall population (4+), children (4–18), and adults (19+). ResultsThe proportion of dietary intakes (grams) that were covered by CPI prices significantly increased from the national short list to the national long list but did not significantly differ from the national long list to the provincial long list. The national short list resulted in the highest daily and energy-adjusted diet costs overall. No difference in diet costs was noted between the national and provincial long lists. Diet costs for 4 food groups—additions, sweets, fruits, and vegetables, which were poorly covered by the national short list—significantly differed using the national and provincial long lists. All 3 diet cost methods were significantly correlated with energy intakes; however, a strong/very strong correlation was detected for children, and a weak/moderate correlation for adults. ConclusionsThe choice of food price data may introduce bias in the diet cost estimate, as well as limiting our understanding of how individuals allocate their diet costs. Refinement of diet cost estimation methodology and measures can strengthen future studies of how consumers allocate their purchases to their diets.

Inferring local social cost from renewable zoning decisions. Evidence from Lower Austria’s wind power zoning

Large infrastructures, such as wind turbines, may adversely affect their environment, so their deployment is often regulated. These regulations are frequently based on a dichotomy between areas considered feasible or infeasible areas for infrastructure deployment. To overcome the inability of such a binary distinction to adequately represent the involved economic trade-offs between, but also within feasible and infeasible areas, we establish a discrete choice framework to elicit social preferences implicit in Lower Austria’s wind power zoning and generate comprehensive estimates of local social costs in high spatial resolution. Our findings suggest that wind turbines were attributed significant local social costs in the political zoning process. These local social cost estimates can inform siting decisions, improve power system modelling and open a novel perspective on the assessment of potentials for renewable energies.

Reshaping water distribution topology from the carbon emission reduction perspective: An exploratory analysis of water distribution reliability

As urban economies continue to evolve, the water distribution networks (WDNs) are expanding in scale and becoming more interconnected, leading to increased carbon emissions from operations and maintenance. Consequently, enhancing the stability and safety of WDNs while saving energy has emerged as a primary research focus. This study abandoned the original use of high economic costs for post-maintenance of WDNs. Instead, it reshaped the traditional water distribution topology to form a dynamic, storable, energy-efficient "WDN self-help" model. Drawing inspiration from the "deep tunnel" project in drainage systems, the proposal was to leverage underground spaces to create a deep aqueduct (DA) complementing the traditional WDN, forming a three-dimensional (3D) WDN. Hydraulic and water quality analyses of varying scales of the 3D WDN model demonstrated its superior ability to equalize node pressures, reduce pipeline head losses, and maintain water quality for end-users. Reliability assessments of the 3D WDN revealed enhanced system robustness for medium-to large-scale distributions, while energy consumption analyses indicated a significant increase in water supply energy utilization and significant long-term reductions in carbon footprint. A practical case study was presented to validate the effectiveness of the 3D WDN concept, confirming its ability to reliably distribute water even in the event of a failure. Finally, an estimate of the retrofit cost and the static payback period of the 3D WDN was conducted. This study aims to provide a theoretical reference for the renovation of water supply projects or the optimal design of new WDNs in the context of carbon neutrality.

Human-animal contact to inform zoonotic disease risk across gradients of agricultural land use change in the Central River Region (CRR) of The Gambia (ZooContact): a formative study.

Pilot studies are important initial steps in research, providing a preliminary assessment of the practicality, feasibility, and potential challenges of a proposed study. This study attempts to assess the feasibility, practicality, and acceptability of a study that integrates a human-animal contact (HAC) questionnaire, animal biodiversity survey using acoustic analysis, and zoonotic disease investigation in animals among rural households in the Central River Region (CRR) of The Gambia. The pilot study revealed granular insights that would otherwise go unnoticed, providing vital information that directly guided the design and implementation of the subsequent full-scale study on zoonotic disease risk. A pilot study was conducted in five villages in the CRR of The Gambia. Community sensitization was carried out together with the village leadership, followed by a familiarization tour of the study setting. Questionnaire-based interview was conducted among participants (n = 50) randomly selected to assess the acceptability and reliability of the questionnaire. The feasibility and acceptability of biodiversity surveys and animal sampling were assessed using verbal inquiries from participants and community leaders. The recruitment rate was 96%, and most participants, 50 out of 52, were willing to participate without compensation for lost time during interviews. For animal sampling, 45 out of 50 participants were willing to allow the study team to sample blood and feces from their animals without any form of incentive. All five village heads agreed to the usage of sound recorders to be placed within their community for animal biodiversity assessment. For the survey effort, one field assistant interviewed 25 participants per week. It took a total of 1 h to complete an interview, including random household selection, consenting, and questionnaire interview. The pilot study confirmed the feasibility of the research and informed the design of the larger study. Key parameters, such as community access, acceptability, recruitment success, and logistical requirements, contributed to robust sample size calculations and realistic project cost estimates. Additionally, the study enabled the research team to familiarize themselves with the communities and refine the methods for the full study.

SP5.9 - A cost-benefit analysis of a digital post-operative integrated care plan app for surgical patients

Abstract Aims To study the cost-benefit analysis of a digital post-operative integrated care plan app for surgical patients. Methods 1. Preliminary data from patient survey - we designed a questionnaire to assess patients’ views of the Post Op app. 2. Estimates for NHS services cost - derived from the King’s Fund latest report (2023) and the NHS Digital National schedule of reference costs (2017, 2021-22). 3.Estimates for travel-associated costs - We assumed a total cost per mile of 16p, and also assumed the patients would need to pay an average cost of £1.6/h for hospital parking for an average of 3h per visit. We assumed a carbon emission of 221.4 grams per mile (Department for Transport data). 4.Modelling approach - We used a conservative modelling approach simulating different patient groups with varying levels of postoperative anxiety/complications. Results Taking into account avoidable presentations to ED, costs borne by the patients, lost productivity, environmental costs, avoidable re-operations and the costs related to antibiotic tolerance/resistance, the lower boundary of total savings from a digital post-operative follow-up tool equates to £58,739 per 100 patients and the upper boundary is £79,949 per 100 patients. Conclusion Post Op application provides excellent support for most patients in the immediate postoperative period and is likely to result in a significant reduction in the number of contacts patients make with the GP or hospital, and with the Emergency Department resulting in significant cost saving for both the service and the patients. Furthermore, earlier recognition, monitoring and appropriate treatment of SSIs provides further savings whose magnitude is likely underestimated.

SP4.5 - Cost estimates of intra-operative cell salvage in patients undergoing major liver surgery: a retrospective cohort study

Abstract Aims Major liver surgery is associated with a high risk of blood loss. Autologous transfusion of blood salvaged intra-operatively (cell salvage) reduces the requirement for post-operative allogenic transfusion. Allogenic transfusion is associated with risks, and blood is a scarce and costly resource. However, the cost of cell salvage in liver resection has not been previously estimated. Objective To estimate the cost of cell salvage in patients undergoing major liver surgery. Methods We analysed a cohort of 243 patients who underwent major liver surgery between 2015 and 2022 at a large tertiary referral hospital in England. Cost of cell salvage was calculated as an average price for consumables and operator time. Cost of admission including cell salvage was assessed per year. Results The average cost of cell salvage per patient was £433. On average, consumables costed £240 and costs associated with operating cell salvage machinery were £193. The average cost for an index admission for this cohort of patients undergoing major liver surgery with cell salvage was £24,694. When comparing the required units of allogeneic blood required to replace the red cells lost during surgery, cell salvage led to cost-savings in one of the years under analysis. Conclusions Our findings suggest that cell salvage has the potential to be cost-effective in patients undergoing major liver surgery. These findings should be assessed in an economic evaluation conducted alongside a randomised controlled trial.

Foslevodopa/foscarbidopa (LDp/CDp) in advanced Parkinson’s Disease (aPD): demonstration of savings from a societal perspective in the UK

Aims In advanced Parkinson’s disease (aPD), adequate 24-hour control of OFF-time may not be achievable using oral/transdermal therapies. Clinical trials of foslevodopa/foscarbidopa (LDp/CDP) demonstrate meaningful reductions in OFF-time and OFF-related sleep disturbance in aPD. Previous analyses have only considered direct medical costs: this analysis considers a broader societal perspective (direct non-medical costs, informal care, loss of earnings, productivity, and tax). Methods Inputs for the societal impact model were taken from a cost-utility model comparing LDp/CDp with best medical treatment (BMT), accepted by the UK National Institute of Health and Care Excellence (NICE). Quintiles of normalized OFF-time across a 16-hour waking day in each treatment group were applied to literature-based estimates for direct medical, non-medical, and indirect costs. The resulting state-specific cost estimates were applied to the modelled aPD patient population. Results The model estimates the potential UK population for LDp/CDp at 17,505. Continuous 24-hour delivery of LDp/CDp results in greater time spent in OFF-time states 0–1 (0–4 hours of OFF-time/16-hour waking day) vs BMT alone. Net savings if all eligible patients receive LDp/CDp are £79.1 M in year 1, £235.4 M in year 2, rising to £262.2 M in year 3, declining to £222.9 M in year 4 and £153.7 M in year 5 as disease progresses and the efficacy of LDp/CDp declines. The estimated total net savings are £953 M after 5 years. Results are robust in scenario analyses (excluding costs of excessive sleepiness, earnings loss, productivity, and tax loss). Limitations A NICE-accepted model was used as the economic modelling basis for the societal impact model, however, much of the data was derived from Adelphi datasets, with the potential for inconsistent definitions. Conclusion When considered from a societal perspective, the use of LDp/CDp in aPD patients inadequately controlled on oral therapy is associated with net healthcare and societal annual savings of over £79.1 M vs BMT.

A practitioner's guide to estimate overland transportation costs*

Poor infrastructure and high domestic shipping costs are often cited as important impediments to economic activity in developing countries. Domestic shipping being mostly overland, understanding the level and structure of costs in road freight transportation could thus help formulate policies that aim to lower them. This review provides a summary of overland transport cost estimates with a focus on trucking, the dominant mode of domestic freight. By describing conceptual issues, highlighting sources of data and alternative methodologies with their key findings, it is intended to help practitioners and researchers navigate the literature.

Radial Basis Function (RBF) and Multilayer Perceptron (MLP) Comparative Analysis on Building Renovation Cost Estimation: The Case of Greece

Renovation of buildings has become a major area of development for the construction industry. In the building construction sector, generating a precise and trustworthy cost estimate before building begins is the greatest challenge. Emphasizing the value of using ANN models to forecast the total cost of a building renovation project is the ultimate objective. As a result, building firms may be able to avoid financial losses as long as there is as little discrepancy between projected and actual costs for remodeling works in progress. To address the gap in the research, Greek contractors specializing in building renovations provided a sizable dataset of real project cost data. To build cost prediction ANNs, the collected data had to be organized, assessed, and appropriately encoded. The network was developed, trained, and tested using IBM SPSS Statistics software 28.0.0.0. The dependent variable is the final cost. The independent variables are initial cost, estimated completion time, actual completion time, delay time, initial and final demolition-drainage costs, cost of expenses, initial and final plumbing costs, initial and final heating costs, initial and final electrical costs, initial and final masonry costs, initial and final construction costs of plasterboard construction, initial and final cost of bathrooms, initial and final cost of flooring, initial and final cost of frames, initial and final cost of doors, initial and final cost of paint, and initial and final cost of kitchen construction. The first procedure that was employed was the radial basis function (RBF). The efficiency of the RBFNN model was evaluated and analyzed during training and testing, with up to 6% sum of squares error and nearly 0% relative error in the training sample, which accounted for roughly 70% of the total sample. The second procedure implemented was the method called the multi-layer perceptron (MLP). The efficiency of the MLPNN model was assessed and examined during training and testing; the training sample, which made up around 70% of the overall sample, had a relative error of 0–7% and a sum of squares error ranging from 1% to 5%, confirming specifically the efficacy of RBFNN in calculating the overall cost of renovations.