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The essential investments in new product development (NPD) made by industrial companies entail effective management of NPD activities. In this context, performance measurement is one of the means that can be employed in the pursuit of effectiveness.

The purpose of this paper is to compare the performance of regression and artificial-neural-networks (ANNs) methods to estimate the running cost of building projects towards improved accuracy.

A data set of 20 building projects is used to test the performance of these two (ANNs/regression) models in estimating running cost. The concept of cost-significant-items is identified as important in assisting estimation. In addition, a stepwise technique is used to eliminate insignificant factors in regression modelling. A connection weight method is applied to determine the importance of cost factors in the performance of ANNs.

The results illustrate that the value of the coefficient of determination=99.75 per cent for ANNs model(s), with a value of 98.1 per cent utilising multiple regression (MR) model(s); second, the mean percentage error (MPE) for ANNs at a testing stage is 0.179, which is less than that of the MPE gained through MR modelling of 1.28; and third, the average accuracy is 99 per cent for ANNs model(s) and 97 per cent for MR model(s). On the basis of these results, it is concluded that an ANNs model is superior to a MR model when predicting running cost of building projects.

A means for continuous improvement for the performance of the models accuracy has been established; this may be further enhanced by future extended sample.

This work extends the knowledge base of life-cycle estimation where ANNs method has been found to reduce preparation time consumed and increasing accuracy improvement of the cost estimation.

The paper provides an overview of research published in the innovation and operations management (IOM) literature on 15 methods for cost management in new product development, and it provides a comparison to an earlier review of the management accounting (MA) literature (Wouters & Morales, 2014).

This structured literature search covers papers published in 23 journals in IOM in the period 1990–2014.

The search yielded a sample of 208 unique papers with 275 results (one paper could refer to multiple cost management methods). The top 3 methods are modular design, component commonality, and product platforms, with 115 results (42%) together. In the MA literature, these three methods accounted for 29%, but target costing was the most researched cost management method by far (26%). Simulation is the most frequently used research method in the IOM literature, whereas this was averagely used in the MA literature; qualitative studies were the most frequently used research method in the MA literature, whereas this was averagely used in the IOM literature. We found a lot of papers presenting practical approaches or decision models as a further development of a particular cost management method, which is a clear difference from the MA literature.

This review focused on the same cost management methods, and future research could also consider other cost management methods which are likely to be more important in the IOM literature compared to the MA literature. Future research could also investigate innovative cost management practices in more detail through longitudinal case studies.

This review of research on methods for cost management published outside the MA literature provides an overview for MA researchers. It highlights key differences between both literatures in their research of the same cost management methods.

This article surveys the literature dealing with theory and applications of life cycle costing (LCC). It deals with the literature published in the last 25 years and provides 667 references.

To provide an overview of research published in the management accounting literature on methods for cost management in new product development, such as a target costing, life cycle costing, component commonality, and modular design.

The structured literature search covered papers about 15 different cost management methods published in 40 journals in the period 1990–2013.

The search yielded a sample of 113 different papers. Many contained information about more than one method, and this yielded 149 references to specific methods. The number of references varied strongly per cost management method and per journal. Target costing has received by far the most attention in the publications in our sample; modular design, component commonality, and life cycle costing were ranked second and joint third. Most references were published in Management Science; Management Accounting Research; and Accounting, Organizations and Society. The results were strongly influenced by Management Science and Decision Science, because cost management methods with an engineering background were published above average in these two journals (design for manufacturing, component commonality, modular design, and product platforms) while other topics were published below average in these two journals.

The scope of this review is accounting research. Future work could review the research on cost management methods in new product development published outside accounting.

The paper centers on methods for cost management, which complements reviews that focused on theoretical constructs of management accounting information and its use.

This paper proposes an intact framework for building life cycle energy estimation (LCEE), which includes three major energy sources: embodied, operational and mobile.

A systematic review is conducted to summarize the selected 109 studies published during 2012–2021 related to quantifying building energy consumption and its major estimation methodologies, tools and key influence parameters of three energy sources.

Results show that the method limitations and the variety of potential parameters lead to significant energy estimation errors. An in-depth qualitative discussion is conducted to identify research knowledge gaps and future directions.

With societies and economies developing rapidly across the world, a large amount of energy is consumed at an alarming rate. Unfortunately, its huge environmental impacts have forced many countries to take energy issues as urgent social problems to be solved. Even though the construction industry, as the one of most important carbon contributors, has been constantly and academically active, researchers still have not arrived at a clear consensus for system boundaries of life cycle energy. Besides, there is a significant difference between the actual and estimated values in countless current and advanced energy estimation approaches in the literature.

The purpose of this paper is to discuss life cycle cost management and highlight the practical challenges related to collecting adequate data and practicing long‐term cost management in an uncertain environment.

The paper reports a case study conducted in the Finnish Defence Forces. As part of the case study, a life cycle cost model for a case product was developed.

Activity‐based life cycle cost modeling can provide relevant information for varying product management needs at different stages in the life of a product. Quantification of uncertainty is one of the elements in the modeling that can improve the feasibility of LCC both for cost estimation and tracking purposes.

Only a few empirical studies on life cycle costing have been reported which focus on the defence sector. The paper contributes to our understanding of how LCC can be used in a continuous manner and depicts how LCC can produce a sharpened cost image of a particular product.

This paper aims to identify the main non-cost factors affecting accurate estimation of life cycle cost (LCC) in building projects.

Ten factors affecting LCC in building project cost estimates are identified through literature and interviews. A questionnaire survey is conducted to rank these factors in order of priority and provide the views of cost practitioners about the significance of these factors in the accurate estimation of LCC. The data from 138 construction building projects completed in UK were collected and analysed via multiple regression to discover the relationship between capital and LCCs and between non-cost factors and cost estimation at each stage of the life cycle (capital, operation, maintenance and LCC).

The results of analysis of existing LCC data of completing project and survey data from cost professionals are mostly consistent with many literature views and provide a reasonable description of the non-cost factors affecting the accuracy of estimates.

The value of this study is in the method used, which involves analysis of existing life data and survey data from cost professionals. The results provide a plausible description of the non-cost factors affecting the accuracy of estimates.

Reliability analysis is required to identify the components or subsystems with low reliability for a given designed performance. Life cycle cost analysis helps understand the cost implications over the entire life span of a product. The purpose of this paper is to present a case study describing reliability analysis and life cycle cost optimization of a band saw cutting machine manufactured and used in India.

The data required for reliability analysis is collected from the manufacturer and users of band saw cutting machine. The parameters of failure distribution have been estimated by using ReliaSoft’s Weibull++6 software. The life cycle cost is divided into various cost elements such as acquisition cost, operation cost, failure cost, support cost and net salvage value.

The results of the analysis show that the components such as band wheel bearing, guide roller bearing, limit switch, carbide pad, hydraulic cylinder oil seal, control panel dial, control panel and solenoid valve are critical from reliability and life cycle cost analysis perspective.

With certain design changes it is found that the reliability of the system is increased by 15.85 percent while the life cycle cost is reduced by 22.09 percent. The study also shows that the reliability analysis is useful for deciding maintenance intervals.

The purpose of this paper is to conduct life-cycle cost analysis of a short-haul underground freight transportation (UFT) system for the Dallas Fort Worth international airport.

The research approach includes: identifying the cost components of the proposed airport UFT system; estimating life-cycle cost (LCC) of system components using various methods; determining life-cycle cash flows; evaluating the reliability of the results using sensitivity analysis; and assessing the validity of the results using analogues cases.

Although the capital cost of constructing an airport UFT system seems to be the largest cost of such innovative projects, annual costs for running the system are more significant, taking a life-cycle perspective. System administrative cost, tunnel operation and maintenance, and tunnel construction cost are the principle cost components of the UFT system representing approximately 46, 24 and 19 percent of the total LCC, respectively. The shipping cost is estimated to be $4.14 per ton-mile. Although this cost is more than the cost of transporting cargos by trucks, the implementation of UFT systems could be financially justified considering their numerous benefits.

This paper, for the first time, helps capital planners understand the LCC of an airport UFT system with no or limited past experience, and to consider such innovative solutions to address airport congestion issues.