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Fluctuations in the tender price index have an adverse effect on the construction sector and the economy at large. This is largely due to the positive relationship that exists between the construction industry and economic growth. The consequences of these variations include cost overruns and schedule delays, among others. An accurate forecast of the tender price index is good for controlling the uncertainty associated with its variation. In the present study, the efficacy of using an adaptive neuro-fuzzy inference system (ANFIS) for tender price forecasting is investigated. In addition, the Box–Jenkins model, which is considered a benchmark technique, was used to evaluate the performance of the ANFIS model. The results demonstrate that the ANFIS model is superior to the Box–Jenkins model in terms of the accuracy and reliability of the forecast. The ANFIS could provide an accurate and reliable forecast of the tender price index in the medium term (i.e. over a three-year period). This chapter provides evidence of the advantages of applying nonlinear modelling techniques (such as the ANFIS) to tender price index forecasting. Although the proposed ANFIS model is applied to the tender price index in this study, it can also be applied to a wider range of problems in the field of construction engineering and management.

The prices of construction resources (construction cost) have been increasing faster than construction output prices (construction price) in Hong Kong since the mid‐1970s, giving rise to a long‐term divergence between the two price trends. As the difference has existed for quite a long time, it cannot be adequately explained by a short‐term change in supply and demand conditions. The present paper introduces the major indices that reflect the trends of the prices of construction resources and outputs in Hong Kong. It also attempts to explain, from an economic point of view, the major factors which contributed to the divergence between the long‐term trends of the prices of construction resources and outputs. One of the conclusions is that, for the past 25 years, the productive efficiency of the Hong Kong building industry has benefited from and been greatly upgraded by imported construction technologies, as well as by a burgeoning quality of human resources. The data and examples quoted in the present paper are sided towards building construction. Therefore, the scope of investigation of this paper, strictly speaking, is confined to the building industry, and does not include the building services and civil engineering subsectors. However, because of the higher degree of mechanization and faster technological progress in the civil engineering and building services subsectors, the present author believes that the results and conclusions should also be applicable to the whole construction industry.

The purpose of this paper is to investigate the whole-life costs of non-residential green-rated building developments in Singapore to derive useful information for research and practice. When industry stakeholders like building owners, architects, engineers, quantity surveyors, builders and facility managers have detailed information about the initial and operating costs of different types of buildings, they will be able to apply whole-life costing to their existing or new projects with the intention of achieving value for money, as well as environmental sustainability. The developed index is useful to green policymakers and building owners.

Data are collected from building projects certified by the Building and Construction Authority (BCA) of Singapore under the Green Mark scheme, starting from 2005. Statistical analysis is performed on the collected data to generate the information required to build the index as well as cost database. The Paasche price index method is used to produce a weighted composite index for Singapore’s non-residential building sector.

The results show the classification of whole-life costs components by two main groups – “development and construction costs”, and “operating and maintenance costs”. There are a total of 68 cost significant items selected from 13 construction work categories. Comparing the weights for three non-residential building types, the highest is obtained for industrial building, which is followed by institutional and commercial buildings.

Without data, the description of the research has primarily dealt with the formulation of the proposed index because designing an appropriate methodology is key to ensure widespread acceptance and use.

Prospective users have to be aware that the index cannot provide information about change in absolute terms and is not very accurate as such in reflecting the actual level of costs or prices of the variable of interest. However, it is a good indicator of the relative change over time in the level of costs or prices.

It is expected that this method contributes additional information to BCA’s existing tender price index about a building’s operating costs as well since the proposed index is a measure of change in the average whole life-cycle costs of buildings over time.

Tender price remains an imperative parameter for clients in deciding whether to invest in a construction project, and it serves as a basis for tender price index (TPI) manipulations. This paper aims to examine the factors affecting tender price in the construction industry.

Based on the literature review, nine independent constructs and one dependent construct relating to tender pricing were identified. A structured questionnaire survey was conducted among quantity surveyors in Ghana. Partial least squares structural equation modelling (PLS-SEM) examined the influences of various constructs on tender price development (TPD) and the relationships among TPD and TPI.

Results showed that cultural attributes, client attributes, contractor attributes; contract procedures and procurement methods; consultant and design team; external factors and market conditions; project attributes; sustainable and technological attributes; and TPI have a positive influence on tender price, whereas fraudulent attributes exert a negative influence.

The findings offer construction professionals broader understanding of factors that affect tender pricing. The results may be used in professional decision-making in the pricing of construction projects, as they offer clearer causal relations between how each construct will influence pricing.

This study adds to the body of construction pricing knowledge by establishing the relationships and degree of influences of various factors on tender price. These findings provide a valuable reference for practitioners.

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.

The main objective of this study is to initiate general building cost indicators to serve as cost indicators for the construction industry in Egypt. The two models (Egypt 1 and Egypt 2 Indices) developed for building the indices in this paper have been derived based on the “Engineering News Record” (ENR) Indices model with modifications to better suit the Egyptian market. Egypt 1 Indices is comprised of three indices which serve as a general cost indicator for the construction industry price movement in Egypt. Egypt 2 Indices is comprised of two indices which serve as a construction cost indicator for the reinforced concrete structures price movement in Egypt. The period analyzed in this research is 11 years (1988 through to 1998). The validation of index numbers produced showed that each index does indeed represent the respective type of building for which it was computed. Further, the analysis of Egypt Indices compared to the ENR Indices revealed that both indices exhibited trends that are generally similar from the year 1992 up to 1998.

The aim of this article is to develop a cost index to serve as a price indicator for the Egyptian construction industry.

The model (Egypt 1 indices) developed for building the indices in this paper has been derived based on the “Engineering News Record” (ENR) indices model with modifications to better suit the Egyptian market. Egypt 1 indices are comprised of three indices, which serve as a general construction price indicator for the construction industry price movement in Egypt. The period analyzed in this research is 11 years (1988 through 1998).

Validation of Egypt 1 indices numbers produced in this paper showed that each index does indeed represent the respective type of building for which it was computed. Further, the analysis of Egypt 1 indices compared to the ENR indices revealed that both indices exhibited trends that are generally similar from the year 1992 up to 1998 (the last year included in this study).

This research has the potential to introduce the use of construction cost indices and to put these into practice. This should help aid contractors and other construction parties operating in Egypt with an adequate tool for pricing and estimation of projects.