Relevant bibliographies by topics / Project cost estimation

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Project cost estimation'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Project cost estimation"

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Ekung, Samuel, Adeniran Lashinde, and Emmanuel Adu. "Critical Risks to Construction Cost Estimation." Journal of Engineering, Project, and Production Management 11, no. 1 (January 1, 2021): 19–29. http://dx.doi.org/10.2478/jeppm-2021-0003.

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AbstractThe prevalence of cost overrun in project delivery suggests an acute dearth of inclusive understanding of the effect of risks on construction cost estimation. In aberrant to the generic assumptions, customary to inquiries in construction risk researches, this paper appraised critical construction estimating risks. The study evaluated the sources, frequency and significance of construction estimating risks, using data from a questionnaire survey of 206 quantity surveyors in Nigeria. The data were analysed using factor analysis, Fussy Set Theory, Terrell Transformation Index (TTI), and Kruskal Wallis H tests. The results showed that estimating risks are correlate seven principal sources, namely: estimating resources, construction knowledge, design information, economic condition, the expertise of estimator, geographic factor, cost data, and project factors (λ, > 0.70 <1.0). Twenty-nine risk factors likewise emerged critical construction estimation risks (TTI, 69-87 > 65 percent) and the top three were low construction knowledge, inaccurate cost information and changes in government regulations (factor scores > 0.60 > 0.50). The awareness and accurate assessment of these risks into project cost estimation would reduce cost overrun. The study, therefore, recommends synergies between projects’ internal/ external environments for proper scoping of these risks into project estimates.
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Sonmez, Rifat. "Conceptual cost estimation of building projects with regression analysis and neural networks." Canadian Journal of Civil Engineering 31, no. 4 (August 1, 2004): 677–83. http://dx.doi.org/10.1139/l04-029.

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Conceptual cost estimates play a crucial role in initial project decisions, although scope is not finalized and very limited design information is available during early project stages. In this paper, the advantages and disadvantages of the current conceptual cost estimation methods are discussed and the use of regression, neural network, and range estimation techniques for conceptual cost estimation of building projects are presented. Historical cost data of continuing care retirement community projects were compiled to develop regression and neural network models. Three linear regression models were considered to identify the significant variables affecting project cost. Two neural network models were developed to examine the possible need for nonlinear or interaction terms in the regression model. Prediction intervals were constructed for the regression model to quantify the level of uncertainty for the estimates. Advantages of simultaneous use of regression analysis, neural networks, and range estimation for conceptual cost estimating are discussed.Key words: conceptual cost estimation, regression analysis, neural networks, range estimation.
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Kitchenham, Barbara A., and N. R. Taylor. "Software project development cost estimation." Journal of Systems and Software 5, no. 4 (November 1985): 267–78. http://dx.doi.org/10.1016/0164-1212(85)90026-3.

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Galli, Brian J. "Cost Estimation Methods in Quality Management and Continuous Improvement." International Journal of Service Science, Management, Engineering, and Technology 12, no. 1 (January 2021): 38–61. http://dx.doi.org/10.4018/ijssmet.2021010103.

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This paper investigated cost estimation methods and continuous improvement in terms of project management planning, as well as the factors that influenced these actions. Estimating the cost was one of the most imperative tasks to be done by the managers for a project. Key factors, such as cost, size, schedule, quality, people resources, maintenance costs, and complexity, were usually estimated in the beginning of project development. The techniques used for cost estimation included data composed from past projects that were combined with mathematical formulae to get the closest estimation. In regards to continuous improvement, the four-step quality model (PDCA cycle) was used as an ongoing effort to improve products or services. PDCA stands for plan, do, check, and act, which were the steps to successfully implement change. Notably, project management, when tasked with cost estimation and continuous improvement, was challenged to cope with evolving and situational alterations, which required a different set of skills.
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Yang, Ming, Yuan Li, and Yong Chao Wang. "Using Gray Forecasting Estimates Cost of Aviation Project." Materials Science Forum 532-533 (December 2006): 725–28. http://dx.doi.org/10.4028/www.scientific.net/msf.532-533.725.

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China aviation project has little sample and the traditional method can not estimate the project cost accurately. This paper proposes a method estimating aviation project cost based on gray systematic theory. We divide aviation product into systems or parts and regard them as cost estimation unit. The gray forecasting model GM (1, 1) was set up based on historical cost data of cost estimation unit. If the model’s precision doesn’t meet with the requirement of aviation project cost estimation, the revision model GM (1, 1) must be set up to raise the estimation precision The experimental results show the method can get the more high-accuracy estimation value using the little sample and is suitable for the cost estimation of the our country aviation project.
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Sridarran, Pournima, Kaushal Keraminiyage, and Leon Herszon. "Improving the cost estimates of complex projects in the project-based industries." Built Environment Project and Asset Management 7, no. 2 (May 11, 2017): 173–84. http://dx.doi.org/10.1108/bepam-10-2016-0050.

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Purpose Project-based industries face major challenges in controlling project cost and completing within the budget. This is a critical issue as it often connects to the main objectives of any project. However, accurate estimation at the beginning of the project is difficult. Scholars argue that project complexity is a major contributor to cost estimation inaccuracies. Therefore, recognising the priorities of acknowledging complexity dimensions in cost estimation across similar industries is beneficial in identifying effective practices to reduce cost implications. Hence, the purpose of this paper is to identify the level of importance given to different complexity dimensions in cost estimation and to recognise best practices to improve cost estimation accuracy. Design/methodology/approach An online questionnaire survey was conducted among professionals including estimators, project managers, and quantity surveyors to rank the identified complexity dimensions based on their impacts in cost estimation accuracy. Besides, in-depth interviews were conducted among experts and practitioners from different industries, in order to extract effective practices to improve the cost estimation process of complex projects. Findings Study results show that risk, project and product size, and time frame are the high-impact complexity dimensions on cost estimation, which need more attention in reducing unforeseen cost implications. Moreover, study suggests that implementing a knowledge sharing system will be beneficial to acquire reliable and adequate information for cost estimation. Further, appropriate staffing, network enhancement, risk management, and circumspect estimation are some of the suggestions to improve cost estimation of complex projects. Originality/value The study finally provides suggestions to improve cost estimation in complex projects. Further, the results are expected to be beneficial to learn lessons from different industries and to exchange best practices.
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Kurasova, O., V. Marcinkevičius, V. Medvedev, and B. Mikulskienė. "Early Cost Estimation in Customized Furniture Manufacturing Using Machine Learning." International Journal of Machine Learning and Computing 11, no. 1 (January 2021): 28–33. http://dx.doi.org/10.18178/ijmlc.2021.11.1.1010.

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Accurate cost estimation at the early stage of a construction project is a key factor in the success of most projects. Many difficulties arise when estimating the cost during the early design stage in customized furniture manufacturing. It is important to estimate the product cost in the earlier manufacturing phase. The cost estimation is related to the prediction of the cost, which commonly includes calculation of the materials, labor, sales, overhead, and other costs. Historical data of the previously manufactured products can be used in the cost estimation process of the new products. In this paper, we propose an early cost estimation approach, which is based on machine learning techniques. The experimental investigation based on the real customized furniture manufacturing data is performed, results are presented, and insights are given.
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Emhjellen, Magne, Kjetil Emhjellen, and Petter Osmundsen. "Cost Estimation Overruns in the North Sea." Project Management Journal 34, no. 1 (March 2003): 23–29. http://dx.doi.org/10.1177/875697280303400104.

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Recently, a Norwegian government report on the cost overruns North Sea projects was presented (NOU 1999:11). It concluded that there was a 25% increase in development costs from project sanction (POD, Plan for Operation and Development) to last CCE (Capital Cost Estimate) for the 11 oil field projects investigated. Many reasons like unclear project assumptions in early phase, optimistic interpolation of previous project assumptions, optimistic estimates, and underestimation of uncertainty were given as reasons for overruns. In this paper we highlight the possibility that the cost overruns are not necessarily all due to the reasons given, but also to an error in the estimation and reporting of the capital expenditure cost (CAPEX). Usually the CAPEX is given by a single cost figure, with some indication of its probability distribution. The oil companies report, and are required to do so by government authorities, the estimated 50/50 (median) cost estimate instead of the estimated expected value cost estimate. We demonstrate how the practice of using a 50/50 (median) CAPEX estimate for the 11 projects, when the cost uncertainty distributions are asymmetric, may explain at least part of the “overruns.” Hence, we advocate changing the practice of using 50/50 cost estimates instead of expected value cost estimates for project management and decision purposes.
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Relich, Marcin. "Computational Intelligence for Estimating Cost of New Product Development." Foundations of Management 8, no. 1 (January 1, 2016): 21–34. http://dx.doi.org/10.1515/fman-2016-0002.

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AbstractThis paper is concerned with estimating cost of various new product development phases with the use of computational intelligence techniques such as neural networks and fuzzy neural system. Companies tend to develop many new products simultaneously and a limited project budget imposes the selection of the most promising new product development projects. The evaluation of new product projects requires cost estimation. The model of cost estimation contains product design, prototype manufacturing and testing, and it is specified in terms of a constraint satisfaction problem. The illustrative example presents comparative analysis of estimating product development cost using computational intelligence techniques and multiple regression model.
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Bhawana Verma, Satish Kumar Alaria. "Design & Analysis of Cost Estimation for New Mobile-COCOMO Tool for Mobile Application." International Journal on Recent and Innovation Trends in Computing and Communication 7, no. 1 (January 31, 2019): 27–34. http://dx.doi.org/10.17762/ijritcc.v7i1.5222.

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Software cost estimation is a resource forecasting method, which is required by the software development process. However, estimating the workload, schedule and cost of a software project is a complex task because it involves predicting the future using historical project data and extrapolating to see future values. For cost estimates for software projects, several methods are used. Among the various software cost estimation methods available, the most commonly used technology is the COCOMO method. Similarly, to calculate software costs, there are several cost estimating tools available for software developers to use. But these released cost estimation tools can only provide parameters (i.e. cost, development time, average personnel) for large software with multiple lines of code. However, if a software developer wants to estimate the cost of a small project that is usually a mobile application, the available tools will not give the right results. Therefore, to calculate the cost of the mobile application, the available cost estimation method COCOMO II is improved to a new model called New Mobile COCOMO Tool. The New Mobile COCOMO tool developed specifically for mobile applications is a boon for software developers working in small software applications because it only includes important multipliers that play a vital role in estimating the cost of developing mobile applications. Therefore, the objective of this paper is to propose a cost estimation model with a special case of COCOMO II, especially for mobile applications, which calculates the person-month, the programmed time and the average personnel involved in the development of any mobile app.
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Dissertations / Theses on the topic "Project cost estimation"

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Chu, Xiaoyuan. "Improving Estimation Accuracy using Better Similarity Distance in Analogy-based Software Cost Estimation." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-246116.

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Software cost estimation nowadays plays a more and more important role in practical projects since modern software projects become more and more complex as well as diverse. To help estimate software development cost accurately, this research does a systematic analysis of the similarity distances in analogy-based software cost estimation and based on this, a new non-orthogonal space distance (NoSD) is proposed as a measure of the similarities between real software projects. Different from currently adopted measures like the Euclidean distance and so on, this non-orthogonal space distance not only considers the different features to have different importance for cost estimation, but also assumes project features to have a non-orthogonal dependent relationship which is considered independent to each other in Euclidean distance. Based on such assumptions, NoSD method describes the non-orthogonal angles between feature axes using feature redundancy and it represents the feature weights using feature relevance, where both redundancy and relevance are defined in terms of mutual information. It can better reveal the real dependency relationships between real life software projects based on this non-orthogonal space distance. Also experiments show that it brings a greatest of 13.1% decrease of MMRE and a 12.5% increase of PRED(0.25) on ISBSG R8 dataset, and 7.5% and 20.5% respectively on the Desharnais dataset. Furthermore, to make it better fit the complex data distribution of real life software projects data, this research leverages the particle swarm optimization algorithm for an optimization of the proposed non-orthogonal space distance and proposes a PSO optimized non-orthogonal space distance (PsoNoSD). It brings further improvement in the estimation accuracy. As shown in experiments, compared with the normally used Euclidean distance, PsoNoSD improves the estimation accuracy by 38.73% and 11.59% in terms of MMRE and PRED(0.25) on ISBSG R8 dataset. On the Desharnais dataset, the improvements are 23.38% and 24.94% respectively. In summary, the new methods proposed in this research, which are based on theoretical study as well as systematic experiments, have solved some problems of currently used techniques and they show a great ability of notably improving the software cost estimation accuracy.
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Ahiaga-Dagbui, Dominic Doe. "Rethinking construction cost overruns : an artificial neural network approach to construction cost estimation." Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/10454.

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The main concern of a construction client is to procure a facility that is able to meet its functional requirements, of the required quality, and delivered within an acceptable budget and timeframe. The cost aspect of these key performance indicators usually ranks highest. In spite of the importance of cost estimation, it is undeniably neither simple nor straightforward because of the lack of information in the early stages of the project. Construction projects therefore have routinely overrun their estimates. Cost overrun has been attributed to a number of sources including technical error in design, managerial incompetence, risk and uncertainty, suspicions of foul play and even corruption. Furthermore, even though it is accepted that factors such as tendering method, location of project, procurement method or size of project have an effect on likely final cost of a project, it is difficult to establish their measured financial impact. Estimators thus have to rely largely on experience and intuition when preparing initial estimates, often neglecting most of these factors in the final cost build-up. The decision-to-build for most projects is therefore largely based on unrealistic estimates that would inevitably be exceeded. The main aim of this research is to re-examine the sources of cost overrun on construction projects and to develop final cost estimation models that could help in reaching more reliable final cost estimates at the tendering stage of the project. The research identified two predominant schools of thought on the sources of overruns – referred to here as the PsychoStrategists and Evolution Theorists. Another finding was that there is no unanimity on the reference point from which cost performance could be assessed, leading to a large disparity in the size of overruns reported. Another misunderstanding relates to the term “cost overrun” itself. The experimental part of the research, conducted in collaboration with two industry partners, used a combination of non-parametric bootstrapping and ensemble modelling with artificial neural networks to develop final project cost models based on about 1,600 water infrastructure projects. 92% of the validation predictions were within ±10% of the actual final cost of the project. The models will be particularly useful at the pre-contract stage as they will provide a benchmark for evaluating submitted tenders and also allow the quick generation of various alternative solutions for a construction project using what-if scenarios. The original contribution of the study is a fresh thinking of construction “cost overruns”, now proposed to be more appropriately known as “cost growth” based on a synthesises of the two schools of thought into a conceptual model. The second contribution is the development of novel models of construction cost estimation utilising artificial neural networks coupled with bootstrapping and ensemble modelling.
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Theodorakopoulos, Thomas F. "Integrated cost management system for delivering construction projects." Thesis, Loughborough University, 2017. https://dspace.lboro.ac.uk/2134/27629.

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Cost management forms a major discipline in delivering construction projects of different sizes and complexity. Traditional cost management systems are mostly based on principles enacted several decades ago. A notable feature of these traditional cost management systems is that key information required for critical decisions is usually produced too late, and is often too aggregated and configured in a form that is not amenable to the requirements for current project management practice. Other problems associated with traditional cost systems relate to inadequacies in estimating and cost control processes and particularly the lack of integration of cost management across the whole project. The lack of integration means measurements provided by traditional cost systems do not sufficiently align with the goals and objectives set for the project. To address these inherent weaknesses in the current practice of cost management, a number of studies have argued for an integrated alternative that better responds to the information demand and decision making need to be developed. The thesis presents the development of a solution to such an integrated cost management system. The developed solution addresses the gaps of the traditional option by integrating the stages making up the whole life cycle of the project to enable professionals gain an appreciation of the ramifications of any early decisions made. The investigation conducted to support the development of the integrated cost management system and the applied model addresses user requirements and determination of the system boundary conditions for efficacious use by key decision makers. The new cost management system developed achieves a linkage of the planning and control stages into one, with a continuous stream of cost management information in both stages. The integration ensures that cost information is more relevant to the circumstances of the modern project manager.
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Han, Sedat. "Estimation Of Cost Overrun Risk In Interrnational Project By Using Fuzzy Set Theory." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606032/index.pdf.

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In the global construction market, most construction companies are willing to undertake international projects in order to maximise their profitability by taking advantage of attractive emerging markets and minimise dependence on unfavorable domestic market conditions. In order to be awarded a contract in highly competitive global construction market, companies should excel in choosing the most attractive markets and prepare winning bids for the selected construction projects in those markets. While preparing bids, the major concern of companies is to offer an optimum price that will enable them to earn enough profits and win the contract at the same time, where profit making ability is strongly correlated with proper estimation of a risk premium that is added onto the estimated cost of the project. Due to the nature of construction works, there are lots of uncertainties associated with the project, market and country conditions. Therefore, how the profitability of the project changes with occurrence of various risk events, in other words, the sensitivity of project costs to risk events, should be estimated by bidders realistically. In this study, fuzzy set theory is used to estimate cost overrun risk in international projects at the bidding stage. The objective is to propose a methodology which can be used by bidders to quantify cost overrun risk so that a realistic risk premium may be determined. A fuzzy risk rating approach is proposed to quantify cost overrun risk rating, which takes into account of risks characterised in international construction projects. For this purpose, risk sources have been identified and a risk model is put forward by using influence diagramming method. Based on this risk model, a fuzzy risk rating algorithm has been defined and software has been developed to conduct fuzzy risk rating calculations easily. After a decision-maker inserts the necessary inputs related with project and country risk factors, the output of the software is a rating that takes into account of all factors that may affect cost overrun risk in international construction projects. The reliability of the algorithm and developed software have been tested by an application on a real construction project. The proposed methodology and decision support tool have been proved to be reliable for the estimation of cost overrun risk while giving bidding decisions in international markets.
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Malmquist, Daniel. "A probabilistic pricing model for a company's projects." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-1099.

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The company’s pricing is often highly impacted by the estimation of competitors’ project costs, which also is the main scope in this degree project. The purpose is to develop a pricing model dealing with uncertainties, since this is a main issue in the current pricing process. A pre-study has been performed, followed by a model implementation. An analysis of the model was then made, before conclusions were drawn. Project cost estimation foremost, but also probability distribution functions and pricing as a general concept, were investigated in the mainly literary pre-study. Two suitable methods for project cost estimation were identified; Monte Carlo simulation and Hierarchy Probability Cost Analysis. These lead to a theoretical project cost estimation model. A model was implemented in Matlab. It treats project cost estimation, but no other pricing aspects. The model was developed based on the theoretical one to the extent possible. Project costs were broken down in sub costs which were included in a Monte Carlo simulation. Competitors’ project costs were estimated using this technique. To analyse the model’s accuracy was difficult. It differs from the theoretical one in terms of how probability distribution functions and correlations are estimated. These problems depend on projects with shifting characteristics and limited data and time. A solid framework has been created though. Improvement possibilities exist, e.g. more accurate estimates and a model handling other pricing aspects. The major threat is that nobody maintains the model. Anyway, estimates are not more than just estimates. The model should therefore be viewed as a helpful tool, not an answer.
Företagets prissättning påverkas ofta till stor del av estimeringen av konkurrenters projektkostnader, vilket också är huvudområdet i detta examensarbete. Syftet är att utveckla en prissättningsmodell som hanterar osäkerheter, då detta är ett stort problem i rådande prissättningsprocess. En förstudie har utförts, följt av en modellimplementation. En analys av modellen gjordes sedan, innan slutsatser drogs. Projektkostnadsestimering främst, men även sannolikhetsfunktioner och prissättning som ett allmänt koncept, undersöktes i den i huvudsak litterära förstudien. Två lämpliga metoder för projektkostnadsestimering identifierades; Monte Carlo-simulering och Hierarchy Probability Cost Analysis. Dessa ledde till en teoretisk modell för projektkostnadsestimering. En modell implementerades i Matlab. Den behandlar projektkostnadsestimering, men inga andra prissättningsaspekter. Modellen utvecklades baserat på den teoretiska i möjlig utsträckning. Projektkostnader bröts ner i delkostnader som estimerades för konkurrenterna. Dessa ingick i en Monte Carlo-simulering. Konkurrenters projektkostnader estimerades med hjälp av denna teknik. Att analysera modellens noggrannhet var svårt. Den skiljer sig från den teoretiska beträffande hur sannolikhetsfunktioner och korrelationer estimeras. Dessa problem beror på projekt med skiftande karaktärsdrag samt begränsad data och tid. Ett solitt ramverk har dock skapats. Förbättringsmöjligheter finns, t.ex. noggrannare estimat och en modell som behandlar andra prissättningsaspekter. Det huvudsakliga hotet är att ingen underhåller modellen. Hur som helst är estimat inte mer än estimat. Modellen ska därför ses som ett hjälpverktyg, inte ett facit.
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Xu, Shen. "Automatic cost estimation of construction project based on building information modelling : a knowledge-based system approach." Thesis, University of Reading, 2015. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.699790.

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Balram, Sara. "Perceptions of Model-Based Systems Engineering As the Foundation for Cost Estimation and Its Implications to Earned Value Management." Thesis, The University of Arizona, 2012. http://hdl.handle.net/10150/268476.

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Model-based systems engineering (MBSE) is an enterprising systems engineering methodology, which in replacing traditional, document-centric systems engineering methods, has the potential to reduce project costs, time, effort and risk. The potential benefits of applying MBSE on a project are widely discussed but are largely anecdotal. Throughout the System Engineering and Project Management industries, there is a strong desire to quantify these benefits, particularly within organizations that are looking to apply it to their complex, system of systems projects. The objective of this thesis was to quantify the benefits that model-based systems engineering presents, particularly in terms of project cost estimates. In order to quantify this qualitative data, statistical analysis was conducted on collected perceptions from industry experts and professionals. The results of this work led to identifying future research that should be completed in order to make MBSE an industry-wide standard for the development and estimation of projects.
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Pokorný, Martin. "Metody pro odhady náročnosti pracnosti při plánování projektů." Master's thesis, Vysoká škola ekonomická v Praze, 2008. http://www.nusl.cz/ntk/nusl-15573.

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This work is focused on the problem of IS/ICT project cost estimation. Main aim of this work is to design a methodology, which can be use for project cost estimation in the initial part of the project stadium. Defining a basic terms of the project management and describing the most widely use cost estimation metods are the first step to archive main aim. This will be achived by studing literature and relevant articles of the project management. Next step is find an appropriate factors which help to set up the methodology. This factors can derive from a stakeholder's analysis. After definition these factors there si possible to set up a particular methodology. Universality (for a wide group of the projects), accuracy (to determine a particular method) and usability (in the initial part of the project stadium) are the most important criteria to review this methodology. Finally, it is necessary to evaluate the proposed methodology. This can be achieved by comparing the methods recommended in the methodology and the methods actually used for the real project cost estimation. The expected benefits of this work are the most widely use cost estimation metods arrangement and creation of the recommended metodology which can be used to cost estimation of future projects.
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Ceran, Erhan. "A C++ Distributed Database Select-project-join Queryprocessor On A Hpc Cluster." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614311/index.pdf.

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High performance computer clusters have become popular as they are more scalable, affordable and reliable than their centralized counterparts. Database management systems are particularly suitable for distributed architectures
however distributed DBMS are still not used widely because of the design difficulties. In this study, we aim to help overcome these difficulties by implementing a simulation testbed for a distributed query plan processor. This testbed works on our departmental HPC cluster machine and is able to perform select, project and join operations. A data generation module has also been implemented which preserves the foreign key and primary key constraints in the database schema. The testbed has capability to measure, simulate and estimate the response time of a given query execution plan using specified communication network parameters. Extensive experimental work is performed to show the correctness of the produced results. The estimated execution time costs are also compared with the actual run-times obtained from the testbed to verify the proposed estimation functions. Thus, we make sure that these estimation iv functions can be used in distributed database query optimization and distributed database design tools.
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Mizell, Carolyn. "QUANTITATIVE ASSESSMENT OF SOFTWARE DEVELOPMENT PROJECT MANAGEMENT ISSUES USING PROCESS SIMULATION WITH SYSTEM DYNAMICS ELEMENTS." Doctoral diss., University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4291.

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The complexity of software development projects makes estimation and management very difficult. There is a need for improved cost estimation methods and new models of lifecycle processes other than the common waterfall process. This work has developed a new simulation model of the spiral development lifecycle as well as an approach for using simulation for cost and schedule estimation. The goal is to provide a tool that can analyze the effects of a spiral development process as well as a tool that illustrates the difficulties management faces in forecasting budgets at the beginning of a project which may encourage more realistic approaches to budgetary planning. A new discrete event process model of the incremental spiral development lifecycle approach was developed in order to analyze the effects this development approach has on the estimation process as well as cost and schedule for a project. The input data for the key variables of size, productivity, and defect injection rates in the model was based on analysis of Software Engineering Laboratory data and provided for analysis of the effects of uncertainty in early project estimates. The benefits of combining a separate system dynamics model with a discrete event process models was demonstrated as was the effects of turnover on the cost and schedule for a project. This work includes a major case study of a cancelled NASA software development project that experienced cost and schedule problems throughout its history. Analysis was performed using stochastic simulation with derived probability distributions for key software development factors. A system dynamics model of human resource issues was also combined with the process model to more thoroughly analyze the effects of turnover on a project. This research has demonstrated the benefits of using a simulation model when estimating to allow for more realistic budget and schedule determination including an interval estimate to help focus on the uncertainty of early estimates.
Ph.D.
Department of Industrial Engineering and Management Systems
Engineering and Computer Science
Industrial Engineering and Management Systems
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Books on the topic "Project cost estimation"

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Ali, Ifzal. Foreign exchange and fiscal impact of a project: A methodological framework for estimation. [Manila]: Project Economic Evaluation Division, Economics and Development Resource Center, Asian Development Bank, 1990.

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Software estimation best practices, tools, & techniques: A complete guide for software project estimators. Ft. Lauderdale, FL: J. Ross Pub., 2009.

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Trendowicz, Adam. Software Cost Estimation, Benchmarking, and Risk Assessment: The Software Decision-Makers' Guide to Predictable Software Development. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Project estimating and cost management. Vienna, Va: Management Concepts, 2002.

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Sweeting, Jack. Project cost estimating: Principles and practice. Rugby, Warwickshire, UK: Institution of Chemical Engineers, 1997.

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Voutchkov, Nikolay. Desalination Project Cost Estimating and Management. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa, plc, 2018.: CRC Press, 2018. http://dx.doi.org/10.1201/9781351242738.

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Project Management Institute. Practice standard for project estimating. Newtown Square, Pa: Project Management Institute, Inc., 2011.

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Estimation techniques for web projects. Hershey PA: IGI Pub., 2008.

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A, Beasley Reyna, ed. Software project cost and schedule estimating: Best practices. Upper Saddle River, NJ: Prentice Hall, 1998.

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Group, Louis Berger. Desk reference for estimating the indirect effects of proposed transportation projects. Washington, D.C: National Academy Press, 2002.

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Book chapters on the topic "Project cost estimation"

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Murthy, Subbu. "Project Cost Estimation." In The Chief Information Officer's Body of Knowledge, 171–76. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118269114.ch17.

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Trendowicz, Adam, and Ross Jeffery. "Constructive Cost Model—COCOMO." In Software Project Effort Estimation, 277–93. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-03629-8_9.

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Trendowicz, Adam, and Ross Jeffery. "Principles of Effort and Cost Estimation." In Software Project Effort Estimation, 11–45. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-03629-8_2.

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Samset, Knut. "Top-Down Probability-Based Cost Estimation." In Early Project Appraisal, 215–24. London: Palgrave Macmillan UK, 2010. http://dx.doi.org/10.1057/9780230289925_22.

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Sur, Suchintya Kumar. "Estimation and Cost Analysis of Hydropower Project." In A Practical Guide to Construction of Hydropower Facilities, 371–82. First edition. | New York, NY : CRC Press/Taylor & Francis Group, 2019.: CRC Press, 2019. http://dx.doi.org/10.1201/9781351233279-17.

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Mansor, Zulkefli, Saadiah Yahya, and Noor Habibah Hj Arshad. "Success Factors in Cost Estimation for Software Development Project." In Software Engineering and Computer Systems, 210–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22170-5_19.

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Naik, Praveen, and Shantharam Nayak. "Intelligence-Software Cost Estimation Model for Optimizing Project Management." In Advances in Intelligent Systems and Computing, 433–43. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19807-7_42.

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Muratova, Anna, and Irina Ptukhina. "BIM as an Instrument of a Conceptual Project Cost Estimation." In Proceedings of EECE 2019, 469–77. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42351-3_41.

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Ishii, Nobuaki, Yuichi Takano, and Masaaki Muraki. "A Simulation-Based Dynamic Scheduling Method in Project Cost Estimation Process." In Advances in Intelligent Systems and Computing, 261–79. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69832-8_15.

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Wang, Xinzheng, Liying Xing, and Feng Lin. "The Study of Project Cost Estimation Based on Cost-Significant Theory and Neural Network Theory." In Advances in Soft Computing, 31–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01216-7_4.

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Conference papers on the topic "Project cost estimation"

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Jin, Yongqin, Jun Li, Jianming Lin, and Qingzhang Chen. "Software Project Cost Estimation Based on Groupware." In 2009 WRI World Congress on Software Engineering. IEEE, 2009. http://dx.doi.org/10.1109/wcse.2009.268.

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Hamdan, Khaled, Hazem El Khatib, and Khaled Shuaib. "Practical software project total cost estimation methods." In 2010 International Conference on Multimedia Computing and Information Technology (MCIT 2010). IEEE, 2010. http://dx.doi.org/10.1109/mcit.2010.5444853.

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"VISUALIZING SOFTWARE PROJECT ANALOGIES TO SUPPORT COST ESTIMATION." In 6th International Conference on Enterprise Information Systems. SciTePress - Science and and Technology Publications, 2004. http://dx.doi.org/10.5220/0002651200610068.

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Ren, AiHua, and Yun Chen. "COCOMO II Based Project Cost Estimation and Control." In 2015 3rd International Conference on Education, Management, Arts, Economics and Social Science. Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/icemaess-15.2016.265.

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Bargrizan, Ali, and Alberto De Marco. "Estimation of the Project Cost by Nonlinear Method According to Different Managerial Attitudes." In Project Management Development – Practice and Perspectives. University of Latvia, 2016. http://dx.doi.org/10.22364/pmdpp.2016.01.

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Fitzhenry, P. "Enhanced software project management by application of metrics and cost estimation techniques." In IEE Colloquium on Project Management for Software Engineers. IEE, 1995. http://dx.doi.org/10.1049/ic:19951542.

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Daneva, M. "Approaching the ERP Project Cost Estimation Problem: an Experiment." In First International Symposium on Empirical Software Engineering and Measurement (ESEM 2007). IEEE, 2007. http://dx.doi.org/10.1109/esem.2007.72.

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Suliman, Safa Mohammed Ahmed, and Gada Kadoda. "Factors that influence software project cost and schedule estimation." In 2017 Sudan Conference on Computer Science and Information Technology (SCCSIT). IEEE, 2017. http://dx.doi.org/10.1109/sccsit.2017.8293053.

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Du, Zeyan, and Binyong Li. "Construction Project Cost Estimation Based on Improved BP Neural Network." In 2017 International Conference on Smart Grid and Electrical Automation (ICSGEA). IEEE, 2017. http://dx.doi.org/10.1109/icsgea.2017.162.

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Kang, Tai Kyung, Wonyoung Park, and Yoo Sub Lee. "Development Of CBR-Based Road Construction Project Cost Estimation System." In 28th International Symposium on Automation and Robotics in Construction. International Association for Automation and Robotics in Construction (IAARC), 2011. http://dx.doi.org/10.22260/isarc2011/0243.

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Reports on the topic "Project cost estimation"

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Busch, Christopher, Jayant Sathaye, and G. Arturo Sanchez Azofeifa. Estimating the greenhouse gas benefits of forestry projects: A Costa Rican Case Study. Office of Scientific and Technical Information (OSTI), September 2000. http://dx.doi.org/10.2172/764328.

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Tarko, Andrew P., Mario Romero, Cristhian Lizarazo, and Paul Pineda. Statistical Analysis of Safety Improvements and Integration into Project Design Process. Purdue University, 2020. http://dx.doi.org/10.5703/1288284317121.

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RoadHAT is a tool developed by the Center for Road Safety and implemented for the INDOT safety management practice to help identify both safety needs and relevant road improvements. This study has modified the tool to facilitate a quick and convenient comparison of various design alternatives in the preliminary design stage for scoping small and medium safety-improvement projects. The modified RoadHAT 4D incorporates a statistical estimation of the Crash Reduction Factors based on a before-and-after analysis of multiple treated and control sites with EB correction for the regression-to-mean effect. The new version also includes the updated Safety Performance Functions, revised average costs of crashes, and the comprehensive table of Crash Modification Factors—all updated to reflect current Indiana conditions. The documentation includes updated Guidelines for Roadway Safety Improvements. The improved tool will be implemented at a sequence of workshops for the final end users and preceded with a beta-testing phase involving a small group of INDOT engineers.
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Ribeiro, João A., Paulo J. Pereira, and Elísio M. Brandão. A real options model to determine the optimal contractual penalty for a BOT project. CICEE. Universidade Autónoma de Lisboa, 2021. http://dx.doi.org/10.26619/ual-cicee/wp06.2021.

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Public-Private Partnerships (PPP) became one of the most common types of public procurement arrangements and Build-Own-Transfer (BOT) projects, awarded through adequate bidding competitions, have been increasingly promoted by governments. The theoretical model herein proposed is based on a contractual framework where the government grants leeway to the private entity regarding the timing for project implementation. However, the government is aware that delaying the beginning of operations will lead to the emergence of social costs, i.e., the costs that result from the corresponding loss of social welfare. This fact should motivate the government to include a contractual penalty in case the private firm does not implement the project immediately. The government also recognizes that the private entity is more efficient in constructing the project facility and also in running the subsequent operations. The model’s outcome is the optimal value for the legal penalty the government should include in the contract form. Sensitivity analysis reveals that there is a level for each of the comparative efficiency factors above which there is no need to impose a contractual penalty, for a given level of social costs. Finally, the effects of including a non-optimal penalty value in the contract form, which derives from overestimating or underestimating the selected bidder’s real comparative efficiency are examined, using a numerical example. Results demonstrate that overestimating (underestimating) the selected bidder’s real comparative efficiency leads to the inclusion of a below-optimal (above-optimal) value for the legal penalty in the contract and produces effects the government should prevent by estimating the comparative efficiency factors with full accurac.
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Beiter, Philipp C., Paul Spitsen, Walter D. Musial, and Eric J. Lantz. The Vineyard Wind Power Purchase Agreement: Insights for Estimating Costs of U.S. Offshore Wind Projects. Office of Scientific and Technical Information (OSTI), February 2019. http://dx.doi.org/10.2172/1495385.

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Demaestri, Edgardo C., Cynthia Moskovits, and Jimena Chiara. Management of Fiscal and Financial Risks Generated by PPPs: Conceptual Issues and Country Experiences. Inter-American Development Bank, December 2018. http://dx.doi.org/10.18235/0001470.

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This paper discusses the main issues concerning sovereign fiscal and financial risks from public–private partnerships (PPPs) with a focus on contingent liabilities (CLs). It is based on the presentations and discussions that took place during the XI Annual Meeting of the Group of Latin American and the Caribbean Debt Management Specialists (LAC Debt Group), held in Barbados in August 2015. The main issues discussed include PPP risks assessment, institutional framework for PPP risk management, and accounting and reporting of CLs generated by PPPs. Six country cases (Chile, Colombia, Costa Rica, Honduras, Suriname, and Turkey) are presented to illustrate experiences with different degrees of development regarding the management of risks and CLs related to PPPs. The document concludes that PPP risk management should encompass the whole lifecycle of a PPP project, risks need to be identified and CLs must be estimated and monitored, and the institutional capacity of governments to evaluate and manage PPP risks plays a central role in the successful development of PPP contracts. Although institutional capacities in this regard have improved in recent years, estimations of CLs involved in PPPs are not regularly performed, and there is still room for improvement on the assessment, measurement, registration, budgeting, and reporting of risks and CLs related to PPPs.
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6 GeV light source project cost estimating procedure. Office of Scientific and Technical Information (OSTI), October 1985. http://dx.doi.org/10.2172/376368.

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