Profitability Of Project Research Articles

Artificial Intelligence-Enhanced Green Building Design for Environmental Sustainability

Green buildings are those that use sustainable methods of construction to either maintain or improve the local quality of life. Decisions affecting a project's quality, safety, profitability, and timetable are made using Artificial Intelligence (AI) in Green Construction by analyzing data gathered from monitoring the construction site and using predictive analytics. For instance, increased accuracy in weather predictions might lead to more production, less waste, lower costs, and less greenhouse gas emissions. Green building construction is a significant source of carbon dioxide released through the breakdown of carbonates. Researchers have concluded that integrating industrial wastes is crucial in green concrete making due to its benefits, such as reducing the requirement for cement. When planning with concrete, its compressive strength must be considered. Due to their high predictive power, AI algorithms may be used to determine the compressive strength of concrete mixtures. Existing artificial intelligence (AI) models may be evaluated for their modeling process and accuracy to inform the creation of new models that more accurately represent the comprehensive evaluation of setting parameters on model performance and boost accuracy. Potential sources of conflict in this anthropocentric future include climate change and the availability of renewable energy sources. Scientists think there is a connection between the increased emission of greenhouse gases like carbon dioxide (Co2) from the combustion of fossil fuels and the acceleration of climate change and global warming. Research has demonstrated that the building sector is a significant source of atmospheric carbon dioxide (Co2). Construction, building activities, and subpar energy sources have all significantly increased atmospheric CO2. The proposed research set out to measure how well AI in Green Building Construction (AI-GBC) might reduce carbon emissions and utility bills. Artificial intelligence uses SVM and GA to reduce energy use and carbon dioxide emissions. Several statistical metrics, such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Root Mean Squared Log Error (RMSLE), are used to evaluate the AI-GBC's precision. Both Machine Learning (ML) models yielded positive results, with prediction accuracies above 95%. Regarding predicting Co_2, GA models were close to the mark, with an R2 of 0.95. Ninety-six percent will complete a performance analysis, and 97% will conduct a k-fold cross-validation analysis. Cross-validation is used to ensure that the findings of the extended modeling technique are accurate and prevent overfitting.

Hrad a panstvo Šášov v období habsburskej komorskej správy

The Šášov (Sachsenstein) domain was one of the state dominions in the Lower Hungarian mining district, i.e. in present-day Central Slovakia, that were integrated in the complex of state mining enterprises from the late seventeenth century to the mid-nineteenth century. These state estates became an important economic basis for whole mining district under the Habsburg control, especially in supplies with wood, charcoal, beverages, and victuals. The Šášov castle and dominion had been acquired in 1676 –1678 from the impoverished noble Lippay family and was utilized for economic needs of state enterprising in the precious metal production since then. Until the 1770s, the Šášov castle was used as a granary and the residence of domain administration was situated in the Ladomer manor house. The most profitable cameralistic projects on this state domain that are investigated in this paper represented the brewery in Šášovské Podhradie near the castle with beer production for state workers and clerks, the large taphouse for mineworkers in Štiavnické Bane (Siglisberg), and the state wood-yard in Jalná for a wood and charcoal supply of state mines and smelteries. During the eighteenth century, the integration of this domain into the system of state mining enterprising reached a highest peak.

Impact of Liquidity and Risk on Dividend Policy: A Mediating Role of Investment

Purpose: The aim of this study is to analyze the influence of liquidity and risk on dividend policy in the nepalese banking sector, with a specific focus on examining the mediating role of investment in the relationship between liquidity and risk and the dividend policy. Methods/Design: The study uses a questionnaire survey, gathering 356 responses from bank managers in Nepal representing various banking categories. It adopts a descriptive and correlational research design, incorporating regression analysis and structural equation modeling (SEM) using AMOS to achieve its objectives. Findings: The results indicate that investment significantly mediates the relationship between liquidity, risk, and dividend policy. Specifically, firms with higher liquidity and greater risk are more likely to invest in profitable projects, which are expected to lead to increased profit distribution within the banking sector in the future. Implications/Limitations: These insights are valuable for both financial managers and policymakers in the Nepalese banking sector. However, the study is limited to the banking sector in Nepal and may not generalize to banks in other regions or financial systems. Originality: This study provides a unique perspective on the interaction between company risk and dividend policy in Nepalese banks, filling a gap in the literature on risk management and shareholder value within the context of emerging economies.

INOVASI SOFTWARE UNTUK MEMPERKUAT SISTEM INFORMASI MANAJEMEN PADA BANK SYARIAH

This research aims to develop a management information system in Islamic banks through software innovation. In this article, this article discusses operating systems, applications and programming languages, as well as the role of strategic management in Islamic banks. In this research, qualitative methods were used. Qualitative methods use qualitative data and describe it descriptively to evaluate social events, phenomena or situations. Operating systems are grouped by user interface into CUI and GUI, with examples such as DOS, UNIX, and Windows. Application systems, which are designed to process data, include various types of software such as desktop and web applications. Programming languages are a means of communication between humans and machines, including algorithms that are the basis for program design. In addition, this article outlines the development of strategic management in Islamic banks, which focuses on the formulation, implementation and assessment of strategies to ensure compliance with sharia principles. In this context, information technology plays an important role in increasing financial efficiency and inclusion. The application of artificial intelligence at Bank Syariah Indonesia shows a positive impact on customer experience and operational efficiency. Sharia financial product innovations were also discussed, highlighting the importance of SWOT analysis and customer relationship management (CRM) strategies in facing competition. Finally, this article notes the challenges Islamic banks face in identifying profitable projects and adapting to developments in digital banking technology.

A Second Chance for Failed Projects Using Data Envelopment Analysis Based on Project Attractiveness Factors

Assessing project profitability using Net Present Value (NPV), Internal Rate of Return (IRR), and Modified Internal Rate of Return (MIRR) is a common practice. However, these metrics often overlook key differences between new and existing projects, leading to potential data uncertainty and the failure to capture the complex interrelationships among influencing factors. This paper introduces data envelopment analysis (DEA) as a supplementary tool to identify the most efficient year within a project’s lifecycle, optimize inputs and outputs, and evaluate the factors most impacting the efficiency of decision-making units (DMUs). By optimizing these values, the paper reexamines NPV, IRR, and MIRR to allow for a comparison with the original assessment. If profitability improves, the project becomes more attractive, with the modified inputs and outputs serving as the new benchmark. A case study of a non-viable road project demonstrates this approach. While NPV, IRR, and MIRR showed improvement, the project remained unappealing under optimal conditions. Additionally, a simulated dataset, based on case study parameters, revealed enhanced profitability and new project viability when analyzed. With revised input and output values, the project’s appeal and viability were significantly improved.

Financial Sustainability and Technology Integration in Oil & Gas Cooperatives: Opportunities and Challenges

The oil and gas sector remains a critical component of the global economy, contributing significantly to energy supply, employment, and economic development. However, with growing environmental concerns, market volatility, and operational complexities, maintaining sustainable operations has become increasingly challenging for industry players. This paper delves into the role of financial sustainability and technology integration within oil and gas cooperatives, focusing on the opportunities and challenges that arise from this dual approach. The paper highlights the importance of cooperatives in addressing these challenges by ensuring operational efficiency, fostering innovation, and promoting sustainable development. The integration of advanced technologies such as Artificial Intelligence (AI) and the Internet of Things (IoT) offers substantial benefits for cooperatives operating in the oil and gas sector. These technologies enable organizations to optimize resource allocation, streamline operational workflows, and implement predictive maintenance models to reduce downtime and equipment failure. Furthermore, IoT-based monitoring systems ensure real-time visibility of key operational metrics, allowing for proactive risk management. Financial sustainability, on the other hand, involves implementing robust financial models to manage cash flows effectively, forecast economic risks, and align business strategies with market demands. The interplay between financial sustainability and technology integration allows cooperatives to maximize profitability while reducing environmental impact, contributing to broader sustainability goals. A case study on Shell Nigeria’s Cooperative Society in Port Harcourt is presented to provide practical insights into the application of these principles. The study demonstrates how Shell’s cooperative has utilized IoT-based solutions and predictive financial models to ensure sustainable growth and efficient project execution. The cooperative plays a pivotal role in managing employees’ thrift and loan operations, generating significant value through real estate investments and technology-driven initiatives. By adopting innovative tools and sustainable practices, the cooperative not only ensures operational resilience but also contributes to socio-economic development in the communities it serves. Mathematical models, such as Net Present Value (NPV) analysis, are employed to illustrate the financial optimization strategies used by Shell Nigeria’s cooperative in evaluating project profitability. Diagrams depicting the integration of technology and financial systems further highlight the efficiency and effectiveness of this approach. Through these models, the paper demonstrates how financial decision-making is enhanced, ensuring that investments align with long-term sustainability goals. This study explores the broader implications of integrating technology with financial sustainability in oil and gas cooperatives. It emphasizes the importance of building public-private partnerships to attract investment and foster technological innovation. Additionally, the paper discusses the regulatory landscape and the need for cooperatives to align with global sustainability standards. The findings suggest that cooperatives in the oil and gas sector have a unique opportunity to drive economic resilience and environmental stewardship through effective financial management and advanced technology deployment. The paper provides actionable recommendations for cooperatives seeking to achieve financial sustainability and operational efficiency through technology integration. These recommendations include upskilling employees, enhancing data management capabilities, and establishing strategic partnerships to overcome challenges. The research underscores the importance of cooperatives in achieving sustainable development within the oil and gas sector, making a compelling case for aligning business strategies with emerging technologies and financial best practices. This approach ensures long-term resilience and contributes to broader national and global sustainability goals.

A Comprehensive Study of Techno Economic Viability (TEV) Report of Various Projects

This paper provides a comprehensive analysis of the TEV process, focusing on its application to both greenfield and brownfield projects across various sectors, including manufacturing, infrastructure, energy, and services. The study aims to guide decision-makers by bridging technical assessments with financial analysis to establish project profitability and sustainability. A Techno-Economic Viability (TEV) Study serves as a crucial tool in the decision- making process for both lenders and investors. It offers a detailed assessment of a project's technical feasibility, economic viability, and overall sustainability. It delves into the dual aspects of technical feasibility and economic viability, emphasizing their roles in influencing investment decisions across a wide spectrum of industries, including manufacturing, infrastructure, energy, and services. The findings from this research also illustrate real-world applications, highlighting two case studies with an emphasis on key financial indicators such as the Debt Service Coverage Ratio (DSCR) and Internal Rate of Return (IRR), which are used to measure a project’s ability to meet debt obligations and generate profits. Keywords: Techno Economic Study, Financial Viability, Technical Feasibility, Financial Modelling, Risk Analysis, Investment Decision

Co-Financing the Investment Projects in the field of Public Space Transformation

Introduction. It has become a modern trend to improve the quality of the urban environment using a public-private partnership (PPP) mechanism. By finding a balance between the interests of business and the state on the issues of infrastructure renovation, it is possible to boost the investment processes. Therefore, the PPP as a catalyst for the regional, innovative and social development has been studied in the scientific literature since long ago. Although, many authors recognise the prospects of the PPP efficiency, they still note the need to regularly revise the state support methods and tools, i.e. the existing system of measures requires improvement over time. Special attention has been paid to the models of financing the PPP projects and the ways of investment return. However, the PPP development potential in creation (reconstruction) of the park infrastructure has not been duly revealed yet.Materials and Methods. During the research on identification of the features of the park complex transformation projects reconstructed in the frame of a concession business model, the projects were grouped according to the similarity of features. Then, by comparative analysis method, the problems of full recovery of the investment costs were identified in the selected projects. A hypothesis about the need of using the government budget co-financing for the certain concession agreements targeted at solving the various environmental, educational and awareness-raising issues was put forward.Results. The national practices of transformation of the public spaces, such as parks and park infrastructure, have shown that the most optimal form of the PPP is a concession. The investor uses his funds at the design and construction stages of the creation (reconstruction) of the park complexes. At the stage of facility operation, a private party recovers its costs by collecting fees directly from the consumers. It is important that the expected project profitability should be within 15–25%. Due to the changes in the monetary policy, such profitability at the current key rate is hardly ever possible if the park infrastructure includes a variety of capital-intensive buildings and structures designated not so much for commercial but for social purposes. There arise the risks of receiving less income than expected. Therefore, for such projects, it is necessary to develop the measures expanding the ways of investment return. If a park has a complex infrastructure, which includes the large stadiums, museums, cultural and educational centres, i.e. facilities that are difficult to predict as having a high demand and, thus, not expedient for setting the high fees, it is advisable to combine the direct payment for services with the government budget co-financing. Co-financing is implemented through payment of a capital or operational grants. The variants of a grant can be considered depending on the areas of the park activities (educational, cultural, sport). The operational grant is due to reimburse the operational costs on maintaining the special facilities: adjacent embankments, lighthouses, memorials, etc. For the parks that include the indoor pools, large stadiums, museums, concert halls, it is relevant to use the capital grants to return the investments made into these facilities.Discussion and Conclusion. In the current conditions, the public-private partnership is considered as an alternative to government budget investment into the infrastructure facilities. The transformation of the urban public spaces is also involved in this trend, and there are already positive results achieved. A private party, through investing its own capital, gets the opportunity to operate the created object to recoup its investments. But some projects are difficult in this sense, therefore the interest of the business companies to participate in the improvement of the urban environment quality reduces. In the context of the tight monetary policy, the additional state budgetary measures are needed to stimulate private investments.

Unlocking development of green hydrogen production through techno-economic assessment of wind energy by considering wind resource variability: A case study

Generating hydrogen from renewable energy sources is widely recognized as an effective strategy for addressing critical challenges in the energy sector while contributing to the reduction of greenhouse gas emissions. This study aims to assess the wind energy potential for electricity and hydrogen production in five locations on Sumba Island using 10 years (2011–2020) of data from the NASA's POWER Project. A wind variability assessment was performed on five wind turbines ranging from 500 kW to 1.5 MW and using electrolysis technology. The results indicated a hydrogen production potential of 25–57 tons per year. Economic analysis of hydrogen production for Haharu reveals an attractive internal rate of return (IRR) of 43% with a payback period (PBP) of 2.25 years and a net present value (NPV) of 1.3 MM USD, the levelized cost of electricity (LCOE) of 0.0241 USD/kWh, and the levelized cost of Hydrogen (LCOH) of 1.01 USD/kg. Sensitivity analysis underscores the critical influence of investment and revenue on project profitability, highlighting their substantial impact on determining a project's success or failure. These findings emphasize the potential of Sumba Island as a hub for sustainable energy production to meet the growing demand for clean and renewable energy sources.

A comprehensive review on sand control in oil and gas wells Part I. Mechanical techniques

Sand production is one of the most important problems in the oil and gas industry worldwide and can lead to erosion of surface and downhole equipment, accumulation of sand in wells and facilities, buckling of casing in cased-hole wells, and reduction of well productivity. The erosion of production equipment increases maintenance costs and potential equipment failure. Due to the costs associated with sand control measures and potential production losses, sand production has an impact on project profitability. Environmental concerns can arise if sand-laden produced fluids are discharged untreated, posing a risk to the environment and marine life. To mitigate sand production problems, a variety of sand management and control techniques have been developed and implemented. Over the past several years, sand management and control techniques have advanced considerably due to advances in materials science, well logging, and computational modeling. A better understanding of sand behavior, improved sand control techniques and more accurate predictive models have resulted from these advances. Current developments and strategies in sand management, control and prevention techniques are reviewed in this paper. This review consists of two parts: 1) mechanical techniques and 2) chemical treatment and sand management. Keywords: sand production; gravel packs; pre-packed screens; expandable sand screens; insert screens; patches; chemical consolidation.

Development and implementation of cost control strategies in oil and gas engineering projects

This review delves into the development and implementation of cost control strategies in oil and gas engineering projects, an area critical for maintaining project viability and profitability amidst fluctuating market conditions. Effective cost control is essential in the oil and gas sector, where projects are often capital-intensive and subject to economic and operational uncertainties. This review examines various cost control methodologies and their application throughout the project lifecycle, from initial planning and budgeting to execution and closure. The paper highlights key cost control strategies, including detailed project cost estimation, budget forecasting, and variance analysis. It discusses the use of advanced project management tools and technologies, such as software for real-time cost tracking and predictive analytics, which enhance decision-making and financial oversight. The review also covers the importance of risk management practices in identifying and mitigating potential cost overruns, emphasizing the role of contingency planning and risk assessment in maintaining financial control. Case studies demonstrate how successful implementation of these strategies can lead to significant cost savings, improved project efficiency, and enhanced financial performance. The challenges associated with cost control, including dealing with unexpected price fluctuations, scope changes, and regulatory compliance issues, are also addressed. Solutions to these challenges, such as adopting flexible budgeting techniques and leveraging data-driven insights, are discussed. The review concludes with recommendations for refining cost control practices in oil and gas engineering projects, including the need for continuous monitoring and adjustment of cost control measures, integrating cost management with overall project strategy, and fostering collaboration among project stakeholders to ensure alignment and accountability.

Post-project financial auditing as a continuous improvement tool for SMEs

Post-project financial auditing is a critical tool for ensuring transparency, accountability, and financial accuracy within small and medium-sized enterprises (SMEs). As SMEs navigate project-based operations, it is essential to assess the financial outcomes of completed projects to inform future decision-making and resource allocation. This review explores the role of post-project financial auditing as a continuous improvement tool in SMEs, highlighting its ability to enhance financial discipline, improve cost control, and promote long-term financial sustainability. By examining key aspects of project revenues, expenditures, and profitability, post-project financial audits provide insights into financial performance that are essential for strategic planning. These audits help identify budget deviations, resource misallocations, and cost inefficiencies, enabling SMEs to adjust future financial planning and project management practices. In doing so, audits contribute to refining budgeting processes, promoting data-driven decision-making, and reducing financial risks in subsequent projects. The review also emphasizes the benefits of post-project auditing in fostering a culture of financial responsibility within SMEs. Through the audit process, SMEs can strengthen internal controls, monitor compliance with financial regulations, and ensure that project outcomes align with organizational financial goals. Additionally, the integration of audit findings into future financial strategies enables SMEs to continuously improve their profitability, mitigate risks, and enhance overall financial stability. Despite the clear advantages, challenges such as resource constraints, data management issues, and limited audit expertise can hinder the adoption of post-project audits in SMEs. The review offers practical recommendations to address these challenges, advocating for the use of scalable audit frameworks, digital tools, and ongoing staff training to support effective auditing practices. Ultimately, post-project financial auditing represents a vital mechanism for driving continuous improvement and ensuring the financial resilience of SMEs in an increasingly competitive marketplace.

Public’s Visual Preferences Survey Facilitates Community-Based Design and Color Standards Creation

According to research, there is a disparity in the aesthetic design preferences of the public and architects. This is especially noticeable in urban areas environments, where there is a wide range of demographic variables and a lack of active public involvement in decision-making. The study included a visual preference survey to evaluate the perception and ranking of two dominant color schemes in local development projects in Stockholm across different age, ethnicity, and gender groups from Sweden. Over 400 people participated in the survey, which used photo-elicitation and a literature review. The objective was to determine the extent of divergence and disparities in the ranking of color schemes. The first dominant color schemes are a group of four analogous colors related to the Natural Color System’s (NSC’s) basic colors. The second is a group of four neutral colors that are related to grayscale colors. The study demonstrates that one could also measure building color schemes using visual preference ranking. Moreover, the research introduced a unique method for city planners to understand diverse ethnic, gender, and age group perceptions of color schemes in current projects, promoting active participation in decision-making and providing valuable insights. These insights can enhance people’s sense of belonging, a prerequisite for social sustainability, and improve the quality and profitability of future projects.

Utilizing Project Management Techniques to Model Critical Success Factors in Large-Scale Construction Projects

This study investigates the application of project management techniques to model critical success factors (CSFs) in large-scale construction projects, utilizing Confirmatory Factor Analysis (CFA) to validate the measurement model. Through factor level analysis, eight distinct categories of CSFs were identified, highlighting their significance in project management success. The structural model analysis revealed positive correlations between project management success and CSFs, impacting project-level outcomes such as customer satisfaction, team satisfaction, and project profitability. Strong predictive validity and appropriate model fit were demonstrated through R-squared and Q-squared values, as well as WarpPLS analysis. The study's theoretical implications include a clear differentiation between project management success and project success, while practical implications underscore the importance of leveraging success factors to enhance project outcomes. Overall, the research provides valuable insights for improving the management and performance of large-scale construction projects.

Financial multidimensional assessment of a green hydrogen generation process via an integrated artificial intelligence-based four-stage fuzzy decision-making model

It is widely accepted that there is an urgent need to make green hydrogen (GH2) projects financially viable to reduce global warming. However, any form of improvements to these GH2 projects lead to substantial cost increase. Due to this cost increase, making many improvements negatively affects the financial profitability of hydrogen projects. This is why there is a need for new advanced financial priority analysis tools so that it is easier to develop GH2 projects globally. Accordingly, the aim of this study is to identify and then define the most important factors affecting GH2 generation projects. To achieve this aim, this work proposes a new fuzzy multi-criteria decision-making model based on artificial intelligence (AI). First, experts are weighted with AI technique. Second, the missing evaluations are filled via a recommender system. Third, criteria weights are calculated by the M-SWARA technique integrated with quantum picture fuzzy rough (QPFR) sets. Finally, GH2 energy generation processes are listed by the QPFR-VIKOR approach. Overall, the main contribution of this study is the generation of a comprehensive AI oriented fuzzy decision-making model to make a detailed evaluation with respect to the financial potential improvements of the GH2 generation projects. The main originality of this model is the consideration of AI to calculate the weights of the criteria. Similarly, another benefit of the proposed model, that increases its superiority against other models, is the completion of missing evaluations by experts thanks to the recommender system. It is concluded that the most important criterion affecting green hydrogen investments is organizational effectiveness.

Bayesian optimization for battery electric vehicle charging station placement by agent-based demand simulation

The optimal placement of electric vehicle charging infrastructure (EVCI) is critical for meeting the charging demand of battery electric vehicles (BEVs). However, the questions of how to coordinate the stochastic charging demand and placement of charging infrastructure in an economically effective way and how to solve such a problem on a large real-world scale remain unanswered. This study addresses these questions by developing an agent-based charging station placement model (ACPM) that incorporates demand uncertainty by simulating the behaviors of BEV users. A solution algorithm based on random embedding Bayesian optimization (REMBO) is proposed and shown to significantly improve computational efficiency and solve the ACPM on a large real-world scale. The model and algorithm are applied to a case study of the Atlanta metropolitan area. In the study, the algorithm finds an optimal placement using only 2% of the runtime of existing benchmark methods. This enables the use of the algorithm on a more complex, real-world scale. Results from the case study indicate that the optimal placement of EVCI uses level-2 and direct-current fast charging (DCFC) roughly equally and distributes these relatively evenly throughout the region. This optimal EVCI placement has significant economic benefits because it can improve the expected net present value (NPV) by 50% to 100% relative to common benchmark charging placement practices, such as placing the EVCI uniform randomly or weighted by the number of parked vehicles. Finally, a sensitivity analysis demonstrates that factors such as the size of the BEV market, charging preferences, and charging price are shown to have significant impacts on the optimal placement and profitability of an EVCI project.

Price Cannibalization Effect on Long-Term Electricity Prices and Profitability of Renewables in the Baltic States

This paper aims to evaluate price cannibalization effects in forecasts of long-term electricity prices and substantiate their relevance on the profitability of renewables in the Baltic States from 2024 to 2033. Statistical data analysis, literature review, scenario method, and PLEXOS modeling were applied. Five scenarios were analyzed for developing renewable energy sources (RES) and load in Lithuania. In contrast, scenarios for Estonia and Latvia were based on assumptions derived from the countries’ national RES strategies. The results showed that the increase in RES capacities will halve electricity market prices from around 130 EUR/MWh in 2024 to 58 EUR/MWh in Latvia, 60 EUR/MWh in Estonia, and 60–77 EUR/MWh in Lithuania in 2033. In time-waving, the absolute and relative price cannibalization effects of renewables were found. In 2033, the loss of revenue from solar photovoltaic (PV) generators was estimated to be 5.5–17.0 EUR/MWh in Lithuania, 7.1 EUR/MWh in Latvia, and 5.6 EUR in Estonia. The case of onshore wind demonstrated revenue losses of 10.5–22.0 EUR/MWh in Lithuania, 12.0 EUR/MWh in Latvia, and 10.0 EUR/MWh in Estonia. After 2029, revenues received by RES electricity generators could not guarantee project profitability; therefore, market flexibility options will be required. The key innovative strategy to mitigate the price cannibalization effect is the demand-side response when leveraging demand flexibility. Typically, this is achieved by sending price signals to the consumers who, if they have any, shift their demand to lower price periods. This is easily applied within HVAC systems, smart electric vehicle charging, and smart home appliance usage. Such behavior would allow the price cannibalization effect to be decreased.

Optimal Profitability Analysis for Contractors Regarding Variations in Payment Systems and Scheduling

Construction projects often face higher risks than other types of projects, primarily due to potential delays from inaccurate scheduling and cash flow issues. Therefore, effective scheduling and payment systems are crucial for contractors to reduce risks and achieve optimal profitability. This study aims to identify optimal cash flow and profitability for contractors through the analysis of various payment systems and the utilization of float time. The methods used include cash flow analysis and feasibility analysis using NPV, BCR, and ROI methods. This research explores eight different payment and scheduling approaches to evaluate their impact on project profitability. The results show that cash flow across all alternatives remains positive without experiencing a shortage of funds and indicate that the contractor's optimal profitability is achieved with application of alternative 5, featuring 0% float time and no advance payments. This alternative results in the highest profit, with an NPV of Rp 15,338,960,581, a BCR of 1.059, and an ROI of 5.90%. From these results, it can be concluded that not utilizing float time leads to the most optimal profitability for the contractor. Additionally, it can be said that the scheduling plan implemented by the contractor for the Twin Tower project is well-structured. However, for the payment system, it is recommended to adopt a no-advance payment approach. It is hoped that this study will help contractors optimize their profits in the competitive construction industry.

Developing an efficient planning process for heritage buildings maintenance in Iraq

Abstract Heritage buildings and sites are significant assets for any country, they hold values of the past to the new generation. This research focuses on the problem of deterioration and demolition of heritage buildings due to negligence or aspiration for more profitable projects, which will lead to the loss of valuable heritage buildings. Assuming that this problem can be solved initially from the planning stage, this research aims to enhance the planning process for heritage buildings by specifying the main factors that affect the planning process for the maintenance work and developing a framework of sequential steps for planning process activities to help in creating an efficient plan. The research evaluates the current situation of heritage building conservation in Baghdad, Iraq as a case study, by classifying the relevant categories into maintenance and non-maintenance categories, which describe the reasons that led to the deterioration of numerous local heritage buildings. The results found in this research specify the main factors that lead to an efficient plan that are budget, methods and techniques, level of skills of the workers, schedule, and required materials. A framework for a successive conservation plan is suggested to be adapted, including a series of sequenced processes to get a sound plan. Finally, some recommendations are suggested to develop planning for heritage building conservation, like reevaluating the legislations and laws to enhance the heritage sector, serious work to make the heritage sites take place in the community activities, paying maximum care to the heritage sector by the governmental authorities, and using modern tools in planning in addition to other recommendations.

Combinatorial machine learning approaches for high-rise building cost prediction and their interpretability analysis

ABSTRACT This study focuses on addressing housing gaps in populous southern countries by emphasizing the importance of accurate early cost estimation in construction projects. It compares individual cost prediction models (Decision Tree, BP Neural Network, and Support Vector Machine) with combined prediction models (BP-DT and BP-SVM) for high-rise building cost prediction. The study employs interpretative analysis methods such as the Shapley additive explanation method, partial dependence plots, and individual conditional expectation plots to explore feature interplay and improve model transparency. Results show that the BP-SVM combination algorithm significantly reduces Mean Absolute Error (MAE) compared to other models. Key factors influencing cost estimation include “Estimated project duration” and “Ground floor area”, while others like “Below-ground floors” have minimal impact. The study highlights the interaction of various feature groups on prediction outcomes. Through feature interaction analysis, it is found that the Estimated project duration and Building architecture can have some negative correlation interaction. Estimated project duration and Interior decoration may have to cancel effects Overall, it contributes to construction management by aiding investors in better-assessing project profitability, thereby enhancing investment decision efficiency and quality.