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Electrical services contribute a substantial percentage of total construction cost of any particular project. It is essential for estimators to have a detailed knowledge of the factors that affect the incorporation of electrical services cost into the overall building project cost. The overall aim of the study that formed the basis for this paper therefore was to investigate the factors that influence cost estimating of electrical services project.

The study was carried out based on questionnaire survey of 225 organizations that are involved in cost estimating of electrical services projects in Nigeria. A total of 158 questionnaires out of the 163 retrieved were appropriate for analysis. A list of factors potentially influencing cost estimate for electrical services was identified for the respondents to rate. The data collected were analyzed using factor analysis based on principal component analysis and varimax orthogonal rotation.

The results shows that the factors affecting production of cost estimate for electrical services could be grouped into four principal factors: the most important factor grouping being estimator competence followed by project technicality, economic requirements and contract requirements.

Many factors are considered by practitioners in the preparation of cost estimate for electrical work in construction project development. The paper has listed about 23 factors that are relevant. However, this paper has shown that four principal factors need to be considered as they explain 64 percent of the factors affect cost estimate production for building project's electrical service works.

Review of literature has shown that there is limited empirical research on the factors influencing cost estimate production for electrical services work. The paper has produced an empirical research on the crucial factors that must be taken into account when producing cost estimate for the electrical service projects.

Challenges associated with ensuring the accuracy and reliability of cost estimation of highway construction bid items are of significant interest to state highway transportation agencies. Even with the existing research undertaken on the subject, the problem of inaccurate estimation of highway bid items still exists. This paper aims to assess the accuracy of the cost estimation methods employed in the selected studies to provide insights into how well they perform empirically. Additionally, this research seeks to identify, synthesize and assess the impact of the factors affecting highway unit prices because they affect the total cost of highway construction costs.

This paper systematically searched, selected and reviewed 105 papers from Scopus, Google Scholar, American Society of Civil Engineers (ASCE), Transportation Research Board (TRB) and Science Direct (SD) on conceptual cost estimation of highway bid items. This study used content and nonparametric statistical analyses to determine research trends, identify, categorize the factors influencing highway unit prices and assess the combined performance of conceptual cost prediction models.

Findings from the trend analysis showed that between 1983 and 2019 North America, Asia, Europe and the Middle East contributed the most to improving highway cost estimation research. Aggregating the quantitative results and weighting the findings using each study's sample size revealed that the average error between the actual and the estimated project costs of Monte-Carlo simulation models (5.49%) performed better compared to the Bayesian model (5.95%), support vector machines (6.03%), case-based reasoning (11.69%), artificial neural networks (12.62%) and regression models (13.96%). This paper identified 41 factors and was grouped into three categories, namely: (1) factors relating to project characteristics; (2) organizational factors and (3) estimate factors based on the common classification used in the selected papers. The mean ranking analysis showed that most of the selected papers used project-specific factors more when estimating highway construction bid items than the other factors.

This paper contributes to the body of knowledge by analyzing and comparing the performance of highway cost estimation models, identifying and categorizing a comprehensive list of cost drivers to stimulate future studies in improving highway construction cost estimates.

Cost and time are two of the primary benchmarks in which construction projects are measured. A variety of factors, however, affect cost and time on construction projects, as identified in previous research. This has led to a need for better understanding how factors affecting cost and time overruns on public construction projects can be managed more efficiently. The purpose of this paper is to address these issues.

In this study 26 factors affecting cost and time overruns on construction projects were identified, through qualitative interviews with project managers from Danish governmental agencies and through a literature review. Through principal component analyses the 26 factors were subsequently narrowed down to four primary latent factors.

The identified four latent factors affecting cost and time overruns on public construction projects were lack of quality management, lack of project pre-planning, lack of user management and lack of project management.

Previous research has focussed on increasing knowledge by identifying and ranking factors affecting time and cost performance. This has led to the identification of an overwhelming number of factors to use for managing construction projects. The present research reduced the number of factors by clustering them into key latent factors responsible for most of the deviation in performance, narrowing the scope of construction cost and time management into a few tangible key focus areas. This supports and improves fast decision-making that is necessary in a changeable environment such as construction.

This paper first presents a research framework for e‐service evaluation within four categories: cost, benefit, functions and development, each incorporating a number of factors. Through data analysis and hypotheses testing, inter‐relationships among the factors of the four categories are examined. The results show that the development type of an e‐service has a significant effect on the degree of user satisfaction. Expertise, technique and expense are the principle factors limiting current e‐service adoption. The most significant finding is that, in the development of e‐services, certain cost factors are significantly more important than others in relation to certain benefit factors. The finding is presented as a cost‐benefit factor‐relation model. This provides an insight into whether investment in certain areas of e‐service applications is more important than in others for particular business objectives. These results have the potential to improve the strategic planning of companies by determining more effective investment areas and adopting more suitable development activities where e‐services are concerned.

Overview All organisations are, in one sense or another, involved in operations; an activity implying transformation or transfer. The major portion of the body of knowledge concerning operations relates to production in manufacturing industry but, increasingly, similar problems are to be found confronting managers in service industry. It is only in the last decade or so that new technology, involving, in particular, the computer, has encouraged an integrated view to be taken of the total business. This has led to greater recognition being given to the strategic potential of the operations function. In order to provide greater insight into operations a number of classifications have been proposed. One of these, which places operations into categories termed factory, job shop, mass service and professional service, is examined. The elements of operations management are introduced under the headings of product, plant, process, procedures and people.

The purpose of this paper is to present a new outsourcing model for materials management related to the operating theatre of hospitals. Two distinguishing features characterize the model: the long-term collaborative network established among the supplying companies (the “Network factor”), and the implementation of the RFID technology along the supply chain (the “RFID factor”). The network factor allows sharing transportation costs, while the RFID factor allows implementing a continuous review policy, instead of the periodic review policy normally utilized in hospitals. In the paper the effect of these two factors on the minimization of total materials management costs is investigated.

An analytical model, validated through a simulation study, is proposed to calculate total management costs of materials, depending on the presence of the network and the RFID factors. Throughout the model it is possible to perform a scenario analysis and individuate the inventory management policy that allows minimizing total costs. The procedure has been applied to a real case study of a long-term collaborative network of supplying companies in the healthcare sector that operates in Central Italy.

The optimal inventory management policy strongly depends on the mutual distances of supplying companies and the hospital. Both of the two factors have an impact on the reduction of total annual costs. The analysis of the scenario shows that a positive interaction effect exists between the two factors, so that higher savings are obtained when both factors are present.

The outsourcing model presented in the paper is new, and the managerial insights that can be drawn from the application of the model to the healthcare sector can be extended to many other industries.

This paper aims to identify and analyse the factors affecting the selection of effective cost control techniques in the UK construction industry and assess their importance. The study examines these key areas; the factors that have significant impacts on cost overruns, the most effective cost control techniques and the factors for selecting cost control techniques for a project.

The study relies on a mixed-method research approach; a qualitative exploration of the most effective cost control techniques and the factors affecting the selection of cost control techniques, followed by a questionnaire survey and follow-up interviews. Relative importance index (RII) is used for ranking the factors.

The budgeting technique is ranked first with-0.821RII, followed by cost forecasting-0.800RII and cashflow monitoring-00.733RII, as the most effective cost control techniques. On factors that influenced the choice of the techniques used, cost information/cost-related factors are ranked first with-0.611RII, followed by the size of the company-0.509RII and the effectiveness of the technique-0.572RII.

Although the scope of the study was limited to the UK construction industry, the results could be interpreted for critical learning in other developed/developing countries.

Identifying and ranking the factors affecting the selection of effective cost control techniques in the UK construction industry has been the focal point of this study. The study also proposes a simple but effective model which can be used for critical learning on mitigating cost overruns and the effective use of cost control techniques in the construction industry.

Effective cost performance is a crucial criterion measuring successful project management in public-housing projects. This paper aims to analyse the vital underlying factors surrounding the successful cost management process (CMP) outcomes in public housing projects (PHPs).

The research was conducted in three stages. The first stage consisted of a detailed literature review to document success factors affecting cost performances and management. In stage two, brainstorming sessions were undertaken with construction experts knowledgeable in cost management practices and have been involved in PHPs. These sessions were used to refine those success factors for the PHPs settings and define their criticality with respect to the CMP stages using interpretive ranking process. In stage three, focus group sessions were performed to validate the interrelationships of the contextualised critical success factors.

The top three most critical factors for successful implementation and outcomes at all CMP stages in PHPs settings were found to relate to competencies, team qualities and collaborative practices of the project team. Early contractor involvement and effective construction planning and management also emerged relevant to the process.

Government project departments, project managers and construction organisations (consultants and contractors) need to commit and mandate continuous development of cost management competencies for all professionals engaged in PHPs. Channels supporting team integration and collaborative practices between design and construction teams are required to increase the likelihood of successful project cost management practice and outcomes in PHPs.

The research has developed a factor-process relationship model that can be used to improve and evaluate the efficacy of CMP implementation in PHP settings.

The purpose of this paper is to identify factors affecting cost estimate accuracy in each of five design stages preceding building construction: order of magnitude, conceptual/schematic, detailed design, construction document and bid phase.

Data were collected using an online survey completed by 138 respondents who work in design consultancy firms in Jordan, including project managers, architects and quantity surveyors (QSs). Survey responses were analyzed using descriptive statistics. Confirmatory interviews and case study comparisons were used to confirm the statistical analysis results.

The results of this study indicated that each design stage’s cost estimate was affected by several factors. Two significant factors were common across four of the five design stages: client experience and project team experience. In addition, a high level of agreement was observed among the project managers, architects and QSs regarding the factors affecting cost estimate accuracy.

Accurately estimating building construction costs during the design process has posed a challenge for designers and their clients in Jordan. Despite the care and effort involved in preparing cost estimates in each of the five design stages, deviations are commonly observed. Because the accuracy of building construction cost estimates directly affect the success or failure of a project, the results of this study can be used to reduce uncertainties in building construction cost estimation and subsequently increase the likelihood of project success

This chapter investigates productivity and cost patterns in the all-cargo US air transport sector. We empirically test the productivity growth influence of changes in unexplained technology, air operations movement characteristics, and factor input prices. Findings show productivity trends depicting negative growth for the 1993–2001 sample, then shifting measurably such that productivity trends depict positive growth for the 2002–2014 sample. The post 2001 growth was fueled by changes in unexplained technological advancements. We interpret this finding as an indication of the importance of technological innovation as a performance enhancer in this transport sector. Findings also reveal a lack of productivity change associated with changes in input prices and movement characteristics. We interpret input price findings as indicating increases in factor input prices such as wages and fuel prices are commensurate with enhanced labor and fuel productivity. The movement characteristic findings are attributable to a lack of sustained increases in load factors, stage length, network size and carrying more volume over the network (density).