Uncertainty In Cost Estimates Research Articles

Breaking the Sisyphean loop: reconceptualizing the treatment of risk and uncertainty in transport projects

Worldwide transport projects repeatedly exceed their budgets. This problem has received widespread attention over several decades, with little progress made to improve project cost performance. Consequently, this has led to the emergence of the following recurring question: How can public agencies responsible for delivering transport projects improve the estimation accuracy of their actual construction costs? We use the metaphor of the Sisyphean task to assist us in suggesting that the conflation of risk and uncertainty results in an inability to estimate actual construction costs accurately. Ambiguity aversion, an illusion of certainty, and the repeated occurrence of cost deviations, as demonstrated by our illustrative example and analysis of the elemental cost models of 39 transport projects, collectively create a Sisyphean loop that is impossible to break. Thus, we question the prevailing conceptualisation and treatment of risk and uncertainty used to estimate the actual construction costs of projects. We offer a new theoretical lens framed around ecologically rational heuristics and provide suggestions to reconceptualize and recalibrate the treatment and assessment of uncertainty in cost estimates. We hope this paper provides a much-needed circuit breaker to public agencies’ prevailing treatment of risk and uncertainty and stimulates new lines of inquiry to improve the cost performance of transport projects.

Cost and cost-effectiveness analysis of mass drug administration compared to school-based targeted preventive chemotherapy for hookworm control in Dak Lak province, Vietnam

School-based targeted preventive chemotherapy (PC), the main strategy for soil-transmitted helminths (STH) control, excludes other at-risk populations including adults and preschool children. Mass drug administration (MDA), covering all age groups, would bring additional health benefits but also requires greater investment. This cost survey and cost-effectiveness analysis compared MDA with school-based targeted PC for STH control in Dak Lak, Vietnam, where STH are endemic. A cost survey was conducted in 2020 to estimate the total and per person economic and financial cost of each strategy. Monte Carlo simulation accounted for uncertainty in cost estimates. The primary effectiveness measure was hookworm-related disability-adjusted life years (DALYs) averted, and secondary measures were hookworm infection-years averted and moderate-to-heavy intensity hookworm infection-years averted. A Markov model was used to determine the incremental cost-effectiveness ratio (ICER) of MDA compared to school-based targeted PC using a government payer perspective and a ten-year time horizon. One-way and probabilistic sensitivity analyses (PSA) were performed. Costs are reported in 2020 USD ($). The economic cost per person was $0.27 for MDA and $0.43 for school-based targeted PC. MDA in Dak Lak will cost $472,000 per year, while school-based targeted PC will cost $117,000. Over 10 years, MDA is estimated to avert an additional 121,465 DALYs; 4,019,262 hookworm infection-years, and 765,844 moderate-to-heavy intensity hookworm infection-years compared to school-based targeted PC. The ICER was $28.55 per DALY averted; $0.87 per hookworm infection-years averted, and $4.54 per moderate-to-heavy intensity hookworm infection-years averted. MDA was cost-effective in all PSA iterations. In areas where hookworm predominates and adults suffer a significant burden of infection, MDA is cost effective compared to school based targeted PC and is the best strategy to achieve global targets. The project was funded by the National Health and Medical Research Council (NHMRC) of Australia (Project Grant APP1139561) and JPCDT was supported by a UNSW Scientia PhD Scholarship.

Tracing Hazardous Materials in Registered Records: A Case Study of Demolished and Renovated Buildings in Gothenburg

Hazardous materials encountered during building renovation or demolition processes not only result in uncertainty in cost estimation and the lead time but also hampers material recyclability and reuse. Therefore, the paper discusses the possibility of predicting the extent of the hazardous materials, including asbestos, PCB, mercury, and CFC, through data mining techniques based on registered records. Pre-demolition audits contain observation data that can be used as a sample for statistical prediction through careful processing. By developing an innovative approach of merging data from environmental inventories with building registers, the positive ratio of remaining hazardous materials in the Gothenburg building stock can be estimated. The study highlights the challenges of creating a training dataset by completing information from the existing environmental inventory, providing new insight into digital protocol development for enhancing material circularity.

How to Model Uncertain Service Life and Durability of Components in Life Cycle Cost Analysis Applications? The Stochastic Approach to the Factor Method

The durability of components is characterized by uncertainty, and, consequently, their estimated service life is critical for building project evaluation. Data on the durability of components used as life cycle cost analysis (LCCA) model input are able to influence model construction, model outputs, and residual value calculations. This implies dealing with uncertainty in cost estimates, according to the real estate market dynamics and the economic trends of the construction sector, and in service life estimates during the project time-horizon. This paper acknowledges the methodology presented in previous studies, based on the stochastic global cost calculation. The aim is to propose a methodological step forward by introducing flexibility over time in model input, through a stochastic approach to the Factor Method (FM). This represents an advancement in respect to the FM normed by ISO 15686—part 1:2000. Two different frames, timber and aluminum, as components of a glass façade of an office building project (located in Turin, Northern Italy), are proposed as a case study. The results give full evidence of the capacity of lifespan variables to affect the global cost calculation, overcoming the effects of environmental and financial elements, in contrast with the consolidated literature. The study demonstrates that beta and gamma distributions are preferable when introducing flexibility over time during the building construction processes, confirming the literature on the topic. The methodology adopted is demonstrated to be an effective tool when in presence of alternative investment options, enforcing decision-making in a temporal perspective.

The degree of accuracy and factors that influence the uncertainty of SME cost estimates

ABSTRACTThe study examines the degree of accuracy and factors that influence the uncertainty of cost estimates. A critical review of literature conducted and was followed with two SMEs case studies executing four projects for different clients. The data collection methods used were documental review, observations and interviews. A total of 12 interviews were conducted and analysed using qualitative thematic analysis. The findings reveal an unquantifiable average cost drift or inflated risks of 19% in cost estimates which is significant as compared to other studies. Ten main factors were identified as the influential factors to the uncertainty of cost estimates, which included type of client, terms and conditions of payments, availability of cost information, experience, repeated work and guarantee of the job. This study contributes to existing literature and it reveals that in the UK post-2008 era, cost of construction remains higher and it could be reduced.

Uncertainty in monetary cost estimates for assessing working postures using inclinometry, observation or self-report

ObjectiveTo assess uncertainty in cost estimates for collecting posture data by inclinometry, observations and self-report. MethodIn a study addressing physical workloads at a paper mill, costs were calculated for measuring postures of twenty-eight workers during three shifts. Uncertainty in costs was assessed for all three methods as the range between an assumed best case (lowest cost) and worst case (highest cost) using scenario analysis. ResultsThe cost for observation was larger, but also more uncertain (€16506 and €89552 in the best and worst case, respectively) than that of inclinometry (€7613 - €45896). Self-report costs were both lower and less uncertain (€3743 - €23368). ConclusionsThe extent of uncertainty in cost estimates implies that observation could be less expensive than inclinometry, e.g., in a scenario where experienced observers could use existing software, while inclinometers would have to be purchased. We propose adding uncertainty assessments to cost estimates when selecting a method for measuring working postures, and offer guidance in how to proceed in a specific setting.

Departures from Cost-Effectiveness Recommendations: The Impact of Health System Constraints on Priority Setting

—The methods and application of cost-effectiveness analysis have reached an advanced stage of development. Many decision makers consider cost-effectiveness analysis (CEA) to be a valid and feasible approach toward setting health priorities, and it has been extensively applied in evaluating interventions and developing evidence-based clinical guidelines. However, the recommendations arising from cost-effectiveness analysis are often not implemented as intended. A fundamental reason for the failure to implement is that CEA assumes a single constraint, in the form of the budget constraint, whereas in reality decision makers may be faced with numerous other constraints. The objective of this article is to develop a typology of constraints that may act as barriers to implementation of cost-effectiveness recommendations. Six categories of constraints are considered: the design of the health system; costs of implementing change; system interactions between interventions; uncertainty in estimates of costs and benefits; weak governance; and political constraints. Where possible—and if applicable—for each class of constraint, the article discusses ways in which these constraints can be taken into account by a decision maker wishing to pursue the principles of cost-effectiveness.

Techno-economic and uncertainty analysis of in situ and ex situ fast pyrolysis for biofuel production

This study evaluates the techno-economic uncertainty in cost estimates for two emerging technologies for biofuel production: in situ and ex situ catalytic pyrolysis. The probability distributions for the minimum fuel-selling price (MFSP) indicate that in situ catalytic pyrolysis has an expected MFSP of $1.11 per liter with a standard deviation of 0.29, while the ex situ catalytic pyrolysis has a similar MFSP with a smaller deviation ($1.13 per liter and 0.21 respectively). These results suggest that a biorefinery based on ex situ catalytic pyrolysis could have a lower techno-economic uncertainty than in situ pyrolysis compensating for a slightly higher MFSP cost estimate. Analysis of how each parameter affects the NPV indicates that internal rate of return, feedstock price, total project investment, electricity price, biochar yield and bio-oil yield are parameters which have substantial impact on the MFSP for both in situ and ex situ catalytic pyrolysis.

Economic burden of rotavirus disease in children under 5 years in Kazakhstan

Background We aimed to estimate the societal costs of rotavirus cases among children less than 5 years in Kazakhstan, an upper-middle income country in Central Asia. Methods Data on medical, non-medical and indirect costs were collected for 190 patients less than 5 years, hospitalized with severe diarrhea in 2009 in two pediatric hospitals. Data on resource use for moderate and mild diarrhea cases were obtained from published sources. A probabilistic sensitivity analysis was performed to explore uncertainty in cost estimates. Results Approximately 4,000 severe, 30,700 moderate, and 122,900 mild rotavirus cases were estimated annually in children <5 years old. The mean societal cost of a severe, moderate and mild rotavirus case was estimated at US$ 454, 82, and 21, respectively. The total annual cost of rotavirus disease was $37.53 million or on average $107.36 for a child under 5 years old in Kazakhstan. Ninety-four percent of total costs (35.13 million) are indirect costs (productivity losses) from fatal cases and parents’ job absenteeism, while direct medical costs account for 2.04 million (5.4%), and direct non-medical for 0.46 million (1.2%). Conclusions Rotavirus-associated diarrhea represents a significant economic burden in Kazakhstan, largely due to indirect costs. The costs of rotavirus infections should be considered when planning further preventive actions, including the introduction of rotavirus vaccination.

Conservation Planning when Costs Are Uncertain

Spatially explicit information on the financial costs of conservation actions can improve the ability of conservation planning to achieve ecological and economic objectives, but the magnitude of this improvement may depend on the accuracy of the cost estimates. Data on costs of conservation actions are inherently uncertain. For example, the cost of purchasing a property for addition to a protected-area network depends on the individual landholder's preferences, values, and aspirations, all of which vary in space and time, and the effect of this uncertainty on the conservation priority of a site is relatively untested. We investigated the sensitivity of the conservation priority of sites to uncertainty in cost estimates. We explored scenarios for expanding (four-fold) the protected-area network in Queensland, Australia to represent a range of vegetation types, species, and abiotic environments, while minimizing the cost of purchasing new properties. We estimated property costs for 17, 790 10 × 10 km sites with data on unimproved land values. We systematically changed property costs and noted how these changes affected conservation priority of a site. The sensitivity of the priority of a site to changes in cost data was largely dependent on a site's importance for meeting conservation targets. Sites that were essential or unimportant for meeting targets maintained high or low priorities, respectively, regardless of cost estimates. Sites of intermediate conservation priority were sensitive to property costs and represented the best option for efficiency gains, especially if they could be purchased at a lower price than anticipated. Thus, uncertainty in cost estimates did not impede the use of cost data in conservation planning, and information on the sensitivity of the conservation priority of a site to estimates of the price of land can be used to inform strategic conservation planning before the actual price of the land is known.

Understanding service uncertainties in industrial product–service system cost estimation

The global transition towards service orientation is posing challenges in cost estimation for manufacturers driven by the uncertainties that arise at the bidding stage of long-lasting performance-based contracts (i.e. availability). Service uncertainty is driven by the quality of information flow and knowledge across a given service network; however, it commonly suffers from the unavailability of useful data to assist cost predictions. Currently, consideration of cost uncertainty for an industrial product–service system is lacking in literature. To fill this gap, this paper combines literature in service and uncertainty in cost estimation to propose the components of a service delivery system, classification of sources of uncertainty based on supply and demand and the suitable uncertainty modelling methods for service cost estimation. The paper categorises service uncertainties in a demand and supply approach, whilst also allocating the types of uncertainty into aleatory and epistemic to propose suitable uncertainty modelling approaches. For future research, various areas such as consideration of a holistic approach to account for service uncertainties and development of a framework to support inter-linkages across a service network are proposed.

Joint crisis plans for people with psychosis: economic evaluation of a randomized controlled trial

Objective: To investigate the cost effectiveness of joint crisis plans, a form of advance agreement for people with severe mental illness. Design: Single blind randomised controlled trial. Setting: Eight community mental health teams in southern England. Participants: 160 people with a diagnosis of psychotic illness or non-psychotic bipolar disorder who had been admitted to hospital at least once within the previous two years. Intervention: Joint crisis plan formulated by the patient, care coordinator, psychiatrist, and project worker containing contact information, details of illnesses, treatments, relapse indicators, and advance statements of preferences for care for future relapses. Control group was standardised service information. Main outcome measures: Admission to hospital; service use over 15 months. Results: Use of a joint crisis plan was associated with less service use and lower costs on average than in the standardised service information group, but differences were not significant. Total costs during follow-up were £7264 (€10 616, $13 560) for each participant with a joint crisis plan and £8359 (€12 217, $15 609) for each participant with standardised service information (mean difference £1095; 95% confidence interval -2814 to 5004). Cost effectiveness acceptability curves, used to explore uncertainty in estimates of costs and effects, suggest there is a greater than 78% probability that joint crisis plans are more cost effective than standardised service information in reducing the proportion of patients admitted to hospital. Conclusion: Joint crisis plans produced a non-significant decrease in admissions and total costs. Though the cost estimates had wide confidence intervals, the associated uncertainty suggests there is a relatively high probability of the plans being more cost effective than standardised service information for people with psychotic disorders.

Decision support system for water infrastructure planning under budget uncertainty: A case study from Thailand

: This paper proposes a decision support system (DSS) for long‐term investment planning of water resources infrastructure taking into account the uncertainty inherent in budget availability. The DSS adopts integer goal programming (IGP) to first select the projects that best contribute to the social, economic, and environmental goals of the project areas. Stochastic programming (SP) then selects the budget level that has the highest expected returns for all possible states of the system. The developed DSS recommended planning for a high budget level in the Chiang Mai case study area, which is consistent with the level of funding that was allocated and distributed over the 25‐year analysis period. Uncertainty in cost estimation was also found to play a major role in project selection.

Joint crisis plans for people with psychosis: economic evaluation of a randomised controlled trial

Objective To investigate the cost effectiveness of joint crisis plans, a form of advance agreement for people with severe mental illness.Design Single blind randomised controlled trial.Setting Eight community mental health...

QFD‐ and VE‐enabled target costing: a fuzzy approach

Globalization has provided excellent opportunities for the global manufacturing community together with a stringent barrier on cost control. Target costing has emerged as one of the main tools in aiding the manufacturers to be globally competitive. This paper analyses the effect of tools such as quality function deployment (QFD) and value engineering (VE) on target costing and explores the way in which these tools assist in achieving the target cost. The target costing model developed by Cooper and Slagmulder (Cooper, R. and Slagmulder, R.,Target Costing and Value Engineering, Productivity Press, New York, NY, 1997) has been modified and tools such as QFD and VE have been incorporated in the model. Due to inherent uncertainties in the associated cost of various elements, the model has been further strengthened with the use of fuzzy logic. The theoretical model developed was implemented in an Indian auto component manufacturing company and the results were analysed. Target costing significantly relies upon QFD and VE for its effective implementation. Uncertainty in cost estimation plays a significant role in the target costing process since any variation in cost violates the cardinal rule of target costing, “the target cost should never be exceeded”. Fuzzy logic plays a vital role in accounting for uncertainty in the target costing process and gives a different perspective to arrive at the function cost. A functional approach (VE) combined with QFD backed by fuzzy approach appears to work effectively for a target costing process that is evidenced from the case study. It appears that the model developed will work satisfactorily for an industrial product and the validity of the model for fast moving consumer goods has to be ascertained.

The insurance effect on prescription drug expenditures among the elderly: findings from the 1997 Medical Expenditure Panel Survey.

Despite continuing debate over a prescription drug benefit for the Medicare program, there has been relatively little research estimating the potential cost of providing such a benefit. The objective of this study was to estimate the effect of prescription drug insurance on outpatient prescription drug expenditures among the elderly. We studied respondents aged > or =65 years to the 1997 Medical Expenditure Panel Survey, a representative survey of the U.S. noninstitutionalized population. Survey-weighted linear regression models were used to estimate the probability of any expenditures and total expenditures while controlling for sociodemographic characteristics, chronic conditions, and health status. We used prescription drug insurance status and outpatient prescription drug expenditures. An estimated 34 million elderly people filled 630 million prescriptions in 1997. Thirty-seven percent did not have prescription drug insurance. Total prescription drug expenditures exceeded $23 billion. Persons without prescription drug insurance spent slightly less than $7 billion; those with insurance spent more than $16 billion. After controlling for health status, comorbidity, and demographic characteristics, prescription drug insurance increased expenditures by $183 per person. The marginal increase in total expenditures of extending the average observed benefit to those currently uninsured is $2.3 billion (95% confidence interval, $1.2-3.5 billion). Proposals for a Medicare drug benefit provide high copayments to protect against insurance effects and to address uncertainty in cost estimates of the proposed benefit. By quantifying the insurance effect on expenditures among the elderly, the data reported here could reduce uncertainty in the budget estimation process.

Cost estimation in flat plate processing using fuzzy sets

Cost estimation in Flat Plate Processes (FPP's) involves a combination of man, machine and resources and consequently, a combination of physical processes, engineering resources and economic laws as well as actions and behaviour of people should be taken into consideration. Thus, in cost estimation process, apart from physical and engineering variables, there often exist several subjective criteria, which need to be described qualitatively and linguistically. In addition, there are some probabilistic or random variables including labour fatigue, shortage of resources and materials, failure of machines, unavailability of facilities and so on, which can not be accurately predicted. Using analytical and mathematical approaches, it is not possible to quantify and transform these imprecise and subjective criteria and random factors into proper input variable in the cost estimation model. Therefore, the state of uncertainty should be considered in cost estimation problem in some ways. In this paper, fuzzy sets and probability distribution approaches are applied to tackle the problem of uncertainty in cost estimation in order to generate reliable cost estimates in flat plate processing industry.

Quantification of the effects of spatially varying environmental contaminants into a cost model for soil remediation

In this study we investigated the effects of spatial variability of soil contaminants on cost calculations for soil remediation. Most cost models only provide a single figure, whereas spatial variability is one of the sources to contribute to the uncertainty. A cost model is applied to a study site of 18 ha containing a former gasworks in the Rotterdam harbour. The site was contaminated by heavy metals, PAH and mineral oil. Two sets of environmental thresholds were applied, one for identifying the severeness of contamination and one to decide upon the future use of excavated soil. Three remediation scenarios were compared. Geostatistical simulations were applied, both on individual contaminants and on indicator variables derived from these. As it turns out, spatial uncertainty causes 2–5% uncertainty in the final cost estimates. Another source of uncertainty is the direction of application of the cost model: a least-case approach starts with the lowest threshold value, followed by increasingly higher values, whereas a worst-case approach starts with the highest threshold value followed by decreasing values. Using a worst-case approach yielded cost estimates that were 6–8% higher than cost estimates by a least-case approach. We concluded that 8–13% of the uncertainty in cost estimates could be explained by spatial variation of soil contaminants and lithology.

Differences in bidding strategies

Methodological understanding is increased and the appreciation of discernible competitive bidding strategies widened by investigating the problems of two construction companies, one being a kitchen equipment manufacturer and the other a civil engineering contractor. Detailed strategies are estimated for the former but not for the latter, due primarily to the greater uncertainty in cost estimates for civil engineering contracts producing larger variability in outcomes.