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This paper aims to propose a new format to present the cost of building conservation works which will better reflect the actual cost components and have a higher relevance to building conservation works.

To achieve the study's aim of presenting a new format suitable for building conservation works, a total of 16 conservation projects were selected and work items of the highest frequency were identified and aggregated into the relevant elemental component to formulate a new elemental cost format.

Work items of the highest frequency identified are partitions, doors and ironmongeries, followed by roof finishes and rainwater goods, floor finishes, external walls and windows. In addition to the usual building works, new work items such as scientific analysis, archaeology excavation and temporary roof are also found to be important.

The proposed format has yet to be tested in the local industry, which is necessary to ensure compatibility with industry needs.

This new cost analysis format includes a list of work items that are specific to building conservation works, which may guide the quantity surveyor in preparing a budget/cost estimate with higher accuracy by reducing the risk of omitted work items that are pertinent in building conservation works.

Owing to the lack of cost data information for building conservation works, estimating and controlling the cost in this area of work is very challenging. The proposed new format of elemental cost analysis designed for building conservation works seeks to fill this void by providing a guide in estimating costs for building conservation.

The main purpose of this paper is to systematically identify important factors that are considered in decision making of maintenance cost and discuss how these factors affect maintenance performance.

This paper employs triangulation technique, which combines quantitative and qualitative approaches. The paper starts with the identification of dominant factors through literature reviews followed by semi‐structured interviews with ten building managers and questionnaire survey. A set of questionnaires are distributed to 200 selected buildings managers in Malaysia. The results from 62 completed questionnaires form a database for the quantitative analysis.

This paper concludes that the maintenance performance suffers from the insufficient allocation of maintenance cost. The main factors that are usually considered by the building managers in allocation of maintenance costs are availability of funding, client's preference, and economic situation. Associative test results reveal that variance in maintenance cost could be improved by considering condition of building and complaint about building performance during decision making of maintenance cost.

This paper provides information for building manager on important factors that need to be considered during decision making of maintenance cost allocation. This would help the manager improve effectiveness and accuracy in preparing a maintenance budget.

With the building maintenance sector in Malaysia being conditionally driven and usually carried out only when there is money, it is critical that organization make effective decisions on priority. This paper determines the most important factors in decision making of maintenance budget.

The choice of a particular architectural solution when designing a building considerably influences the costs of its construction. The aim of this paper is to present the indexes which may relate to the complexity of the building shape, and which were then specified and compared on a particular example.

The article analyses various indices of building shape evaluation, their influence on the changes in construction costs and their sensitivity to the changes in the dimensions of the building. The methodology adopted in this article concerns the analysis of the selected simple factors assessing the shape of the building against the cost‐effectiveness of constructing the basic elements of the building.

The authors established the best building shape in relation to the costs of constructing the walls and foundations (square), and to the layout of the inside of the building (rectangle). They believe that the best evaluations of building shape were achieved by the LBI index, which evaluated the shape correctly in all of the analysed examples and which is the most sensitive to the changes in building parameters in correct proportions to the changes in construction costs.

The article presents the indexes which may relate to the complexity of the building shape. The authors established the best building shape in relation to the costs of constructing. The authors provide the degree of the floor area usability in buildings of various shapes.

Although it is easy to show that some buildings cost more to run and operate than others, few people take the trouble to collect evidence and make the comparisons — reflecting the relatively low priority given to buildings in business. Reductions in costs can be significant to company profitability, yet it is a difficult matter to provide a convincing and fully costed argument for making changes to reduce future expenditure, especially where investment is required and where the benefits cannot be easily quantified. Indications are that significant savings are possible in most building costs in use. Indirect cost reductions may be achieved by reorganisation or by encouraging behavioural changes which will enable the building to be used to its full potential. However, direct cost savings may be made by changes to the physical fabric and positive steps can be taken in managing buildings to benefit from these changes and affect profitability. It has been possible to show through action research that the life cycle costs of buildings can be reduced by design, often at no overall capital cost With the availability of suitable tools the future, and its cost consequences, can become an influential factor in management decisions about the building stock.

The accessible nature of straw bale building lends itself well to self-built and workshop-built housing; straw is known to be both relatively inexpensive and easy to work with for people new to construction. A question then arises as to whether or not hiring an experienced builder can reduce overall costs of such a structure. This study conducts a worldwide survey to straw bale home owners to answer this question and to determine general economic data on straw bale homes, such as: what home owners value, who the main builder typically is, and what usually causes budgets to overrun. A key finding is that self-building is economically justified if the projected saving is higher than the cost of a contractor and if the usually longer time needed to build the home is amenable to the investor. An economic case study is also conducted on a straw bale home in Radomlje, Slovenia. All building expenses are categorized by building phase and subgrouped by cost in accordance with accepted building standards. A key observation is how demanding any specific building phase is in comparison to conventional building.

The purpose of this paper is to look at the applications of factor cost indices in the building industry in Nairobi, Kenya against the possibilities established through a review of the principles so as to establish the extent of use in practical situations in the industry. There are two organisations involved in compilation of factor cost indices in Kenya – Central Bureau of Statistics and Joint Building Council (JBC). Their practices for compilation of factor cost indices are reported in this paper.

The paper reviews the principles of factor cost index in order to establish a conceptual framework within which practices are then evaluated. The statistical bureau's compilation of building cost indices and the instructions by the JBC are considered as available evidence of application.

The paper finds that the application of factor cost index in Kenya is limited, a situation that therefore demands more research by the construction industry in Kenya.

The research's originality lies in its supportive evaluation of the application of the indicator concept in the building industry. More applications would imply greater possibilities for research and development within the case study industry.

Developing a reliable cost estimate at the early stage of construction projects is challenging due to inadequate project information. Most of the information during this stage is qualitative, posing additional challenges to achieving accurate cost estimates. Additionally, there is a lack of tools that use qualitative project information and forecast the budgets required for project completion. This research, therefore, aims to develop a model for setting project budgets (excluding land) during the pre-conceptual stage of residential buildings, where project information is mainly qualitative.

Due to the qualitative nature of project information at the pre-conception stage, a natural language processing model, DistilBERT (Distilled Bidirectional Encoder Representations from Transformers), was trained to predict the cost range of residential buildings at the pre-conception stage. The training and evaluation data included 63,899 building permit activity records (2021–2022) from the Victorian State Building Authority, Australia. The input data comprised the project description of each record, which included project location and basic material types (floor, frame, roofing, and external wall).

This research designed a novel tool for predicting the project budget based on preliminary project information. The model achieved 79% accuracy in classifying residential buildings into three cost_classes ($100,000-$300,000, $300,000-$500,000, $500,000-$1,200,000) and F1-scores of 0.85, 0.73, and 0.74, respectively. Additionally, the results show that the model learnt the contextual relationship between qualitative data like project location and cost.

The current model was developed using data from Victoria state in Australia; hence, it would not return relevant outcomes for other contexts. However, future studies can adopt the methods to develop similar models for their context.

This research is the first to leverage a deep learning model, DistilBERT, for cost estimation at the pre-conception stage using basic project information like location and material types. Therefore, the model would contribute to overcoming data limitations for cost estimation at the pre-conception stage. Residential building stakeholders, like clients, designers, and estimators, can use the model to forecast the project budget at the pre-conception stage to facilitate decision-making.

The purpose of this paper is to investigate the commercial aspect of “green” building construction and whether increased investment costs are profitable taking the reduction in operating costs into account. The investment viability is approached by comparing investment in conventional and “green” residential building, particularly passive houses, using real construction and post‐occupancy conditions.

The key data were obtained by surveys and personal interviews. The first survey was directed to the companies which had experience of building low‐energy housing and the second survey to housing companies that actively manage operation of low‐energy houses.

Findings indicate that low‐energy buildings are considered an interesting and sound business opportunity, and investment analysis indicates that low‐energy houses (particularly passive houses) can be more attractive investments than conventional residential buildings. The long‐term strategy of building low‐energy buildings can give competitive advantages. The government initiative and the construction regulations are found to be necessary in eliminating the initial barrier to energy‐efficient projects and achieving long‐term environmental goals.

This paper provides insights into the investment decisions and contributes to the understanding of the construction, operation and profitability of energy‐efficient residential buildings.

Traditionally, early-stage investment decisions on buildings purely based initial capital costs and simply ignored running costs and total lifecycle cost. This was basically due to the absence of estimating models that yield running costs at the early design stage. Often, when the design of a building, which is responsible for 10–15% of its total cost, is completed, 80% of the total cost is committed. This study aims to develop a building characteristic-based model, which is an early-stage determinant of running costs of buildings, to predict the running costs of commercial buildings.

A desk study was carried out to collect running costs data and building characteristics of 35 commercial buildings in Sri Lanka. A Pareto analysis, bivariate correlation analysis and hedonic regression modelling were performed on collected data.

According to Pareto analysis, utilities, services, admin work and cleaning are four main cost constituents, responsible for 80% of running costs, which can be represented by highly correlated building characteristics of building height, number of floors and size. Approximately 94% of the variance in annual running costs/sq. m is expressed by variables of number of floors, net floor area and working hours/day together with a mean prediction accuracy of 2.89%.

The study has utilised a sample of 35 commercial buildings due to non-availability and difficulty in accessing running cost data.

Early-stage supportive running costs estimation model proposed by the study would enable construction professionals to benchmark the running costs and thereby optimise the building design. The developed hedonic model illustrated the variance of running costs concerning the changes in characteristics of a building.

The purpose of this paper is to focus on the ongoing discourse centred on enhancing building performance to provide an interpretation of life cycle cost (LCC) analysis, directly applicable to building construction in coastal areas located in tropical wet–humid settings.

A survey of 50 buildings based on physical observation is carried out to identify typical failure patterns in wet‒humid environment. Further, a comparative initial construction cost and LCC analysis is computed for two alternative building schemes with identical floor plans: Scheme A using sound construction and detailing to guard against future maintenance problems and Scheme B adopting the typical designs evident in the study area.

The result of the analysis shows that in the long-run scheme, A is an economically more viable option than B, as the increased initial costs are entirely offset by the reduced running cost.

The contextual nature of LCC analysis poses difficulties in applying the evidence provided in this study to provide a generalisable financial justification to buildings clients.

The outcome of the study provides analytical validation to overcome resistances and enables informed decision making by clients, which is necessary to promote transition from conventional to environmentally responsive design choices suitable to wet–humid conditions.

The study provides an interpretation of LCC analysis, directly applicable to building construction in the tropical wet–humid setting of coastal areas against the backdrop of inconsistencies in the practical application of the theory of LCC.