Cost-influencing Factors Research Articles

Construction Cost-Influencing Factors: Insights from a Survey of Engineers in Saudi Arabia

Cost overruns represent a continuous challenge within the construction industry, frequently affecting the success of projects. This study explores the factors influencing cost during the construction phase in Saudi Arabia, utilizing data from a survey of 1076 engineers working in the Saudi construction industry. The results identify a number of cost-related factors, including inadequate project management, poor cost estimation, and design errors. Interestingly, some factors, such as currency exchange rate fluctuations and social and cultural influences, were found to have a limited impact on construction costs. Furthermore, the study highlights the role of experience and education level in shaping engineers’ perceptions of these cost factors. The study employs statistical analysis, including Pearson’s chi-squared test, to demonstrate associations between demographics, project characteristics, and cost-influencing factors. The findings suggest the need for refined project management practices, enhanced technical training, and the implementation of digital technologies such as Construction 4.0 to mitigate cost-related risks. This research provides significant insights for construction professionals and policymakers seeking to enhance cost management within the Saudi construction sector, thereby contributing to the ongoing development initiatives aligned with Saudi Arabia’s Vision 2030.

DRG payment for major pancreatic surgery: analysis of resource consumption and suggestions from a tertiary hospital in China.

To investigate the cost homogeneity within the Diagnosis-Related Group (DRG) "major operation of pancreas and liver, with general complications or comorbidities" (HB13), its cost-influencing factors, and to propose suggestions for better grouping efficacy. Medical and insurance settlement data of inpatients covered by the DRG payment system at the author's institution were collected from March 15, 2022 to December 31, 2023. The cost homogeneity of group HB13 was assessed using the coefficient of variation (CV). Clinical factors that may have an impact on hospitalization cost for patients undergoing pancreatic surgery were identified through a semi-structured interview administered to the pancreatic surgeons in author's department, their significance was analyzed using multiple linear regression, along with their impact on the cost of different service categories. A proposal to subdivide HB13 was made and evaluated by CV and t-test. The CV of the HB13 group was 0.4. Robotic-assisted surgery and pancreaticoduodenectomy were two independent factors that significantly affected the total cost. Patients undergoing robotic-assisted surgery have an average increase of 41,873 CNY in total cost, primarily derived from operation fee. Patients undergoing pancreaticoduodenectomy have an average increase of 37,487 CNY in total cost, with significant increases across all service categories. HB13 was subdivided based on whether pancreaticoduodenectomy was performed. The newly formed groups exhibited lower CVs than the original HB13. The cost homogeneity of HB13 was lower than that of other DRG groups in author's department. It is recommended to introduce a supplementary payment for patients requiring robotic-assisted surgery, to guarantee their access to this advanced technology. It is recommended to establish a new group with higher payment standard for patients undergoing pancreaticoduodenectomy. A tiered CV criterion for the evaluation of grouping efficacy is recommended to increase intra-group homogeneity, facilitating a better allocation of health insurance funds, and the prevention of unintended negative outcomes such as service cuts and cherry-picking.

Modeling Cost-Estimation Factors for Public Building Projects with Hybrid Approach in Addis Ababa

Assessing the most important cost-influencing factors is essential for enhancing the predictive ability of cost estimation for building construction projects. The goal of this study is to examine and design a valid cost prediction model for assessing factors that impact the cost estimation of public buildings in Addis Ababa. This research solves these issues that typically arise in predictive cost estimation models in two major processes. First, the insights of 133 professionals gathered on the 38 cost-impacting elements, and 15 top factors design, time or cost, and parties’ experience were determined. The suggested hybrid approach is based on the Akaike information criterion (AIC) and principal component regression (PCR) employed, coupling a stepwise linear regression model. According to the findings of the study, principal component analysis reduced important factors to 14 and efficiently solved the problem of multicollinearity with a variance inflation factor of less than 2, while stepwise cross-validation solved the overfitting problem at the lowest AIC. The cost prediction model sorted out five factors: design completion by the public body when bids are invited; completion of the project scope definition when bids are invited; level of construction complexity; importance of project completion within budget; and subcontractor experience and capability have all been identified as the main cost-determining factors. The study’s contribution is the first approach (PCR–AIC) utilized in this work to explore numerous cost-estimating components, eliminate those that were related to one another, and identify the most crucial ones that consisted of the majority of the original variables’ attributes.

Critical factors influencing the cost in engineering–procurement–construction (EPC) projects: A case study of prefabricated buildings (PBs) in China

Prefabricated buildings (PBs) are a new type of building construction, which are less time-consuming and cause low environmental pollution and resource consumption. They play an important role in industrialized construction and clean production and have gained worldwide attention. However, the high construction costs have become a major obstacle to their popularity and application. This study investigates the factors influencing construction costs of PBs in China using a systematic literature review (SLR), fuzzy interpretive structure modeling (fuzzy ISM), and the Matrice d’Impacts croises-multiplication appliqué an classment (MICMAC) technique. First, 32 influencing factors were identified from the SLR. Second, out of which 16 critical factors were selected and mapped in a hierarchical model through semi-structured interview screening, and the MICMAC technique was used to classify the cost-influencing factors of PBs into different categories. The results revealed that all identified factors played pivotal roles in various capacities and influenced the cost of PB construction. This study may assist administrators and policymakers in better understanding the factors that influence the costs of PBs construction to manage and reduce them.

Construction Project Cost Prediction Method Based on Improved BiLSTM

In construction project management, accurate cost forecasting is critical for ensuring informed decision making. In this article, a construction cost prediction method based on an improved bidirectional long- and short-term memory (BiLSTM) network is proposed to address the high interactivity among construction cost data and difficulty in feature extraction. Firstly, the correlation between cost-influencing factors and the unilateral cost is calculated via grey correlation analysis to select the characteristic index. Secondly, a BiLSTM network is used to capture the temporal interactions in the cost data at a deep level, and the hybrid attention mechanism is incorporated to enhance the model’s feature extraction capability to comprehensively capture the interactions among the features in the cost data. Finally, a hyperparameter optimisation method based on the improved particle swarm optimisation algorithm is proposed using the prediction accuracy as the fitness function of the algorithm. The MAE, RMSE, MPE, MAPE, and coefficient of determination of the simulated prediction results of the proposed method on the dataset are 7.487, 8.936, 0.236, 0.393, and 0.996%, respectively, where MPE is a positive coefficient. This avoids the serious consequences of underestimating the cost. Compared with the unimproved BiLSTM, the MAE, RMSE, and MAPE are reduced by 15.271, 18.193, and 0.784%, respectively, which reflects the superiority and effectiveness of the method and can provide technical support for project cost estimation in the construction field.

New Strategies for Intelligent Computing in Improving the Accuracy of Engineering Costs

Abstract Accurate construction cost calculation is crucial for assessing project viability and selecting design programs. This paper enhances calculation accuracy by first employing the Boruta algorithm to identify vital cost-influencing factors, which serve as the basis for an improved construction cost model. We introduce an enhanced Artificial Neural Network (ANN) model that integrates the AdaBoost algorithm and cost-sensitive methods to refine construction cost estimations. The efficacy of this model is demonstrated through its overall engineering cost error rate of 3.92%, with specific errors in single-side cost, labor, materials, and machinery usage at 3.51%, 7.09%, 3.36%, and 7.93%, respectively. These results meet established accuracy standards, showcasing the model’s potential to significantly improve construction cost management and control.

Socio- and techno-economic analyses of biodiesel production from sewage sludge in Tokyo, Japan

Biodiesel, a promising eco-friendly alternative to diesel, faces a major obstacle in the form of high feedstock costs (50%–70%) for production. Sewage sludge (SS) as a viable feedstock for biodiesel production was recognized due to its abundance, consistent availability, and low cost. However, certain limitations, such as pretreatment and drying, are challenging. This study assessed biodiesel production costs from dewatered and wet SS in Japan, utilizing Aspen Plus for simulations. Estimated costs are 0.09 USD/kg and 0.084 USD/kg for dewatered and wet SS, respectively. Biodiesel prices and cost-influencing factors are analyzed, revealing a potential break-even price as low as 540 USD/t (70% below market price) with a positive net value of 8331 USD. Remarkably, producing biodiesel from SS is found to be nine times cheaper than Japan's current biodiesel production cost. The proposed SS biorefinery strategy, integrated within Japanese WWTPs, is a notable outcome. But the limitations and uncertainties that may affect these results are also highlighted for the reader's consideration.

Single-Cell Protein Production from Industrial Off-Gas through Acetate: Techno-Economic Analysis for a Coupled Fermentation Approach

Third-generation (3G) biorefineries harnessing industrial off-gases have received significant attention in the transition towards a sustainable circular economy. However, uncertainties surrounding their techno-economic feasibility are hampering widespread commercialization to date. This study investigates the production of single-cell protein (SCP), a sustainable alternative food and feed protein, from steel mill off-gas through an efficient coupled fermentation approach utilizing acetate as an intermediate. A comprehensive model that comprises both the gas-to-acetate and the acetate-to-SCP fermentation processes, as well as gas pretreatment and downstream processing (DSP) operations, was developed and used to perform a techno-economic analysis (TEA). Sensitivity analyses demonstrated that significant cost reductions can be achieved by the process intensification of the gas-to-acetate fermentation. As such, an increase in the acetate concentration to 45 g/L and productivity to 4 g/L/h could lead to a potential cost reduction from 4.15 to 2.78 USD/kg. In addition, the influence of the production scale and other economic considerations towards the commercialization of off-gas-based SCPs are discussed. Conclusively, this research sheds light on the practical viability of a coupled fermentation process for SCP production by identifying key cost-influencing factors and providing targets for further optimization of the acetate platform, fostering sustainable and economically feasible bio-based innovations.

Cost estimation model of prefabricated construction for general contractors based on system dynamics

PurposeThe poor capacity of prefabricated construction cost estimation is the essential reason for the low profitability of the general contractor. Therefore, this study aims to focus on the cost estimation of prefabricated construction as the research object. This research aims to enhance the accuracy of total project cost estimation for general contractors, ultimately leading to improved profitability.Design/methodology/approachThis study used Vensim PLE software to establish a system dynamics model. In the modeling process, a systematic research review was used to identify cost-influencing factors; ABC classification and the analytic hierarchy process were used to score and determine the weights of influencing factors.FindingsThe total cost error obtained by the model is less than 2% compared with the actual value. It can be used to cost estimation and analysis. The analysis results indicate that there are 7 key factors, among which the prefabrication rate has the most significant impact. Furthermore, the model can provide the extreme range cost; the minimum cost can reduce by 13% from the value in the case. The factor's value can compose a cost control strategy for general contractors.Practical implicationsThe cost of prefabricated buildings can be estimated well, and deciding the prefabrication rate is crucial. The cost can be declined by correct cost control strategies when bidding and subcontracting are in process. The strategies can follow the direction of the model.Originality/valueA systemic, quantitative and qualitative analysis of cost estimation of prefabricated buildings for general contractors has been conducted. A mathematical model has been developed and validated to facilitate more effective cost-control measures.

Cost overrun estimation in the construction of high-rise buildings using fuzzy inference model

Proper cost forecasting is a major parameter in the success of construction projects, and has a significant impact on various phases of a project, including its budget approval phase. Project managers usually look for solutions to reduce costs. It needs to identify the cost-rising factors, and to exclude them from projects. This study principally aimed at forecasting cost increase of high-rise building construction, using a neuro fuzzy inference model. In fact, the model is able to quantify cost overrun, resulted from each influencing factor, based on fuzzy logic. Through a vast literature review, 43 cost-influencing factors were identified, which then were reduced to 13, using the principal component analysis method, and experts’ opinions. The construction cost was then predicted by the inference model created, based on each factor. The results showed that the factor of “lack of commitment of the Ministry of Housing” had the greatest impact, while the factor of “not considering measures to resolve potential disputes” had the least impact on the estimation of cost overrun in high-rise buildings.

Cost Management for Information and Communication Technology Projects

Information and communication technology (ICT) is an important sector that contributes to the development of a country. However, the success of this sector depends on the success of the ICT projects. Hence, ICT projects must be managed efficiently and effectively to ensure that they are successfully implemented. The literature review reveals that most of the ICT projects around the globe are in a challenged state, especially in terms of cost. This quantitative research aims to explore the cost influencing factors of the ICT projects in Malaysia and to build a cost influencing factors framework as a knowledge base for project managers. A 5-point Likert scale survey was conducted using the purposive sampling and the snowball sampling method to solicit responses from a large population of ICT project managers. The responses of 194 ICT project managers in Malaysia were analyzed, and the top 15 cost influencing factors were identified at different phases of a project. This result was used to build a cost influencing factors framework as a knowledge base for ICT project management.

Analysis of Factors Relevant to Revenue Improvement in Ventral Hernia Repair, Their Influence on Surgical Training, and Development of Predictive Models: An Economic Evaluation.

Background: Ventral hernia repairs (VHR) are frequent but loss- making. This study aims to identify epidemiological and procedure related factors in VHR and their influence on surgical training. Methods: Data from 86 consecutive patients who underwent VHR in 2019 was collected. Moreover, 66 primary ventral hernias and 20 incisional hernias were repaired in open procedures. Linear regression models were made. Results: Primary VHR procedures showed a mean deficit of −378.17 CHF per case. Incisional hernia repair procedures resulted in a deficit of −1442.50 CHF per case. The two hernia groups were heterogeneous. For the primary VHR procedures, the surgery time (β = 0.564, p < 0.001) had the greatest influence, followed by the costs of the mesh (β = −0.215, p < 0.001). The epidemiological factors gender (β = 0.143, p < 0.01) and body mass index (BMI) (β = −0.087, p = 0.074) were also influential. For incisional hernia procedures a surgeon’s experience had the most significant influence (β = 0.942, p < 0.001), and the second largest influence was the price of the mesh (β = −0.500, p < 0.001). The epidemiological factor BMI (β = −0.590, p < 0.001), gender (β = −0.113, p = 0.055) and age (β = −0.026, p < 0.050) also had a significant influence. Conclusion: Our analysis shows a way of improving financial results in the field of ventral hernia repair. Costs can be visualized and reduced to optimize revenue enhancement in surgical departments. In our analysis primary ventral hernias are an appropriate training operation, in which the experience of the surgeon has no significant impact on costs. In primary VHR procedures, revenue enhancement is limited when using an expensive mesh. However, the treatment of incisional hernias is recommended by specialists. The financial burden is significantly higher with less experience. Therefore, these operations are not suitable for surgical training. The re-operation rate decreases with increasing experience of the surgeon. This directly affects the Patient Related Outcome (PROM) and quality of treatment. Therefore, high-quality training must be enforced. Since financial pressure on hospitals is increasing further, it is crucial to investigate cost influencing factors. The majority of Swiss public hospitals will no longer be able to operate ventral hernias profitably without new concepts. In addition to purchasing management, new construction projects, and mergers, improving the results of individual departments is a key factor in maintaining the profitability of hospitals in the future regarding hernia repair without losing the scope of teaching procedures.

Investigation of Cost-Influencing Factors Potentially Controllable by Main Contractors in Construction Projects in Iraq

Cost overrun in construction projects is a common phenomenon in Iraq. This might occur due to diversity of factors. This study aims to identify the factors influencing construction projects cost that are potentially controllable by main contractors. A field study through a questionnaire survey was directed to a sample of related Iraqi professional engineers from general contracting companies at both public and private sectors. Their opinions on the impact and frequency of each factor were investigated. The questionnaire offered (59) factors classified in (8) categories namely; legislations, financial and economic, design, contractual, site management, material, labor and equipment. The factors were ranked according to the highest Relative Importance Index (RII). The study revealed (10) major factors that are potentially controllable by main contractors namely; labor productivity, sub-contractors and suppliers performance, equipment productivity, site organization and distribution of equipment, experience and training of project managers, scheduling and control techniques, planning for materials supply, planning for equipment supply, materials delivery and planning for skilled labor recruitment. Recommendations to aid contractors and owners in early identification of these factors are also included in this study.

Identifying Significant Cost-Influencing Factors for Sustainable Development in Construction Industry Using Structural Equation Modelling

Construction projects are typically conducted in a complex and dynamic environment in which the accumulation of many interrelated factors causes high uncertainty. Many factors may have negative effects on construction projects and thus cause project cost overruns. The aim of this study is to identify significant cost-influencing factors for sustainable development in construction. Considering the effects of economic and environmental factors on project cost is indeed a challenging task due to the shortage of appropriate methodology. This study examines the relationships between cost-influencing factors and construction project cost by using a structural equation model based on the generalized maximum entropy (GME) and Bayesian estimation methods. The advantages of GME and Bayesian methods are discussed, and results obtained from the statistical analysis are provided for illustration. The results can enhance cost performance through the identification and evaluation of the cost-influencing factors. The improved project performance is considered as an important step to transit into a sustainable development in construction. The sustainable development may greatly affect the emission reduction target of the industry.

Cost-influencing risk factors in infrastructure projects on soft soils

In view of economic growth, infrastructure projects are gradually increasing in terms of quantity, size and complexities. As such, construction of infrastructure projects on soft soils is unavoidable. This poses challenges in infrastructure development as infrastructure construction is vulnerable to greater risks. Review of the literature showed that research on risk assessment of infrastructure projects on soft soils is deficient. Hence, this research was focused on cost-influencing risk factors during the construction phase. Analytical hierarchy process (AHP) was used to determine the risk prioritization of infrastructure projects on soft soils through questionnaire survey. It is found that controllable (internal) risk factors, such as legal and project-client risks and uncontrollable (external) risk, such as economic and soil condition risk play a critical role in infrastructure project’s cost on soft soils during the construction stage.

New Zealand Building Project Cost and Its Influential Factors: A Structural Equation Modelling Approach

Construction industry significantly contributes to New Zealand’s economic development. However, the delivery of construction projects is usually plagued by cost overruns, which turn potentially successful projects into money‐losing ventures, resulting in various other unexpected negative impacts. The objectives of the study were to identify, classify, and assess the impacts of the factors affecting project cost in New Zealand. The proposed research model was examined with structural equation modelling. Recognising the lack of a systematic approach for assessing the influencing factors associated with project cost, this study identified 30 influencing factors from various sources and quantified their relative impacts. The research data were gathered through a questionnaire survey circulated across New Zealand construction industry. A total of 283 responses were received, with a 37% response rate. A model was developed for testing the relationship between project cost and the influential factors. The proposed research model was examined with structural equation modelling (SEM). According to the results of the analysis, market and industry conditions factor has the most significant effect on project cost, while regulatory regime is the second‐most significant influencing factor, followed by key stakeholders’ perspectives. The findings can improve project cost performance through the identification and evaluation of the cost‐influencing factors. The results of such analysis enable industry professionals to better understand cost‐related risks in the complex environment.

Economics of public capital expenditure in the Sri Lankan road infrastructure sector

The Sri Lankan Government spends a significant share of its capital budget on road infrastructure. Therefore, it is important to ensure the efficiency of capital deployment in road sector projects. This research was undertaken with the objective of assessing capital efficacy in road development. In addition, the research sought to appraise strategies adopted in the institutionalisation of an appropriate public investment management mechanism, such that the maximum possible economic gain could be obtained. Road projects undertaken by the Road Development Authority of Sri Lanka over the period 2005-2012, covering an overwhelmingly large share of public spending on road sector, were examined. The indicator used as the inverse of capital efficacy was the real capital expenditure intensity per unit of surface area, which was regressed against a selected set of cost-influencing factors, whereby significant determinants of capital intensity were identified. Project size, class of road, nature of terrain, funding mechanism and contract procurement process emerged as significant determinants with their influence being exerted in the expected direction, while the surface technology and the type of contractor were not significant. It was found that to fund projects through bilateral credit tied to contractors domiciled in lender countries without competitive bidding was highly capital intensive, and therefore inefficient, in terms of capital deployment. The outcomes of the study recommend that public investments should be executed through local contractors to the maximum possible extent, and that, whenever foreign funding becomes necessary, contract negotiation with a pre-designated company without competitive bidding should be avoided, given that such a modality would be prone to wastage, leakages, mismanagement, and corruption. It is strongly recommended to institutionalise a competitive procurement process through an effective mechanism for public investment planning, appraisal, and implementation management, to ensure the efficiency of public sector capital expenditure.

Consequential Costs of Occupational Accidents from an Economic and Managerial Perspective: Empirics Results from Austrian

For occupational injuries, the economy, employers, and insurance companies not only face directly related accident costs but also long-term follow-up costs. In Austria, this is the third advanced project on this topic on behalf of the main Austrian occupational insurance company Allgemeine Unfallversicherungsanstalt (AUVA). The team from the University of Vienna reveals cost-influencing factors for the economy, employers, and insurance companies to integrate them into current and future costs of occupational injuries that were acknowledged in a certain year. To do so, the team develops a detailed decision for the support system called “Cost Calculation Tool” that investigates total direct and main indirect costs of individual injury claims from the time of the incident of all injured individuals up to their death. It helps policy makers cluster patients into risk groups to optimally improve the conditions at dangerous and Int Adv Econ Res (2014) 20:351–352 DOI 10.1007/s11294-014-9461-4

An exploration into cost-influencing factors on construction projects

Construction cost overrun is a common problem in construction industries. The objective of this research is to extract the key cost-influencing factors with new concept and methods to help control the expenditure. Hence, this research adopts the Modified Delphi Method (MDM) with 2 groups and 2 rounds and Kawakita Jiro method (KJ) to consolidate the experts' opinions and identify and rank the key factors that affect project costs. Ninety cost-influencing factors are collected from literary review and interviews with experts with practical cost control experiences in the construction companies (Group 1). The KJ method is used to consolidate these factors into 4 categories and down to a total of 42 factors. 2 rounds of questionnaires are then conducted to filter the key factors. In order to verify views of those in the first group, Group 2 consists of experienced experts from the public sectors, consulting firms and construction companies as a comparison. Results of the analysis indicate that there are 16 key cost-influencing factors. Severity Index computation was then adopted to rank these key cost-influencing factors. The study renders that clearly defined scope of project in the contract and cost control are the major determinants for cost overrun.

Reviewing electricity production cost assessments

A thorough review of twelve recent studies of production costs from different power generating technologies was conducted and a wide range in cost estimates was found. The reviewed studies show differences in their methodologies and assumptions, making the stated cost figures not directly comparable and unsuitable to be generalized to represent the costs for entire technologies. Moreover, current levelized costs of electricity methodologies focus only on the producer's costs, while additional costs viewed from a consumer perspective and on external costs with impact on society should be included if these results are to be used for planning. Although this type of electricity production cost assessments can be useful, the habit of generalizing electricity production cost figures for entire technologies is problematic. Cost escalations tend to occur rapidly with time, the impact of economies of scale is significant, costs are in many cases site-specific, and country-specific circumstances affect production costs. Assumptions on the cost-influencing factors such as discount rates, fuel prices and heat credits fluctuate considerably and have a significant impact on production cost results. Electricity production costs assessments similar to the studies reviewed in this work disregard many important cost factors, making them inadequate for decision and policy making, and should only be used to provide rough ballpark estimates with respect to a given system boundary. Caution when using electricity production cost estimates are recommended, and further studies investigating cost under different circumstances, both for producers and society as a whole are called for. Also, policy makers should be aware of the potentially widely different results coming from electricity production cost estimates under different assumptions.