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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.

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.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

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.

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 understand the post-COVID-19 fluctuations in the building construction demand from various angles at the national, regional, and sectoral levels. Despite the significant impact of COVID-19 on the building construction industry, a detailed quantitative analysis of the COVID-19 impact on the building construction demand is still lacking. The current study aims to (1) establish a statistical approach to quantify the COVID-19 impact on the building construction demand; (2) investigate the post-COVID-19 fluctuations in the construction demand of different building services, regional markets, and building sectors using the historical time series of the architecture billings index (ABI); and (3) identify vulnerable market and sector and discuss the post-COVID-19 recovery strategies.

The research methodology follows four steps: (1) collecting national, regional, and sectoral ABIs; (2) creating seasonal autoregressive integrated moving average models; (3) illustrating cumulative sum control charts to identify significant ABI deviations; and (4) quantifying the post-COVID-19 ABI fluctuations.

The results show that all the ABIs experienced a statistically significant decrease after COVID-19. The project inquiries index reduced more but recovered faster than billings and design contracts indices. The midwest billings index decreased the most among the regional ABIs and the commercial/industrial billing index dropped the most among the sectoral ABIs.

This study is unique in the way that it utilized the ABI data and the approach using SARIMA models and CUSUM control charts to assess the post-COVID-19 building construction demand represented by ABI fluctuations.

The purpose of this paper is to examine the features and tendency of cost indices in the global construction setting.

Data from 22 countries/regions are collected and analyzed using maximum variance formulation and Kendall rank correlation coefficient.

It is found that global construction cost indexes (CCIs) have commonly maintained a steady increase for decades, and the CCIs synchronize with each other. Overall synchronicity and synchronicity of different countries pairs have increased with time significantly.

The major limitation, however, is the availability of data: only 22 regions/countries are examined, the distribution of these regions/countries is imbalanced between different continents and various indices are adopted around the world, of which statistical methods are not same.

The implication is that a better perception of CCIs enables contractors to have a robust estimation for bidding prices and to improve the efficiency of construction projects management. The research findings also provide a useful reference for those countries that have not established construction cost indices databases to forecast the tendency of domestic construction industries.

This paper contributes to the overall body of knowledge by presenting the co-movement of global CCIs and measuring the changes of CCI synchronicity with time and in different countries pairs.

This study aims to develop workplace well-being indexes for construction sites of different project types (infrastructure, high-rise and low-rise). Accordingly, the study objectives are to identify the critical factors that affect workplace well-being at construction sites, compare the critical factors between different project types, categorize the critical factors into subgroups and compute indexes for the critical factors and subgroups.

Data from a systematic literature review and semi-structured interviews with construction industry professionals were used to extract 19 potential factors that affect workplace well-being. Then, a structured questionnaire survey was distributed, and 169 valid responses were collected. Finally, the data were analyzed using normalized mean analysis, agreement analysis, factor analysis and fuzzy synthetic evaluation.

The study findings revealed that there are 11, 11, 8 and 12 critical factors across overall infrastructure, high-rise and low-rise construction projects. Out of those, six critical factors are overlapping across project types, including “general safety and health monitoring,” “salary package,” “timeline of salary payment,” “working hours,” “communication between workers” and “planning of the project.” Accordingly, the critical factors can be categorized into two subgroups within each project type. Finally, the development of indexes shows that infrastructure construction projects have the greatest index compared to other project types.

This study contributes to filling the current knowledge gap by developing workplace well-being indexes at construction sites across different project types. The indexes would assist decision-makers in understanding the current state of workplace well-being. This increases the commitment and recognition of well-being across different construction project types.

The purpose of this paper is to examine if temporal aggregation matters in the construction of house price indices and to test the accuracy of alternative index construction methods.

Five index construction models based on the hedonic, repeat‐sales and hybrid methods are examined. The accuracy of the alternative index construction methods are examined using the mean squared error and out‐of‐sample technique. Monthly, quarterly, semi‐yearly and yearly indices are constructed for each of the methods and six null hypotheses are tested to examine the temporal aggregation effect.

Overall, the hedonic is the best method to use. While running separate regressions to estimate the index is best at the broader level of time aggregation like the annual, pooling data together and including time dummies to estimate the index is the best at the lower level of time aggregation. The repeat‐sales method is the least preferred method. The results also show that it is important to limit time to the lowest level of temporal aggregation when construction property price indices.

This paper provides alternative method, the mean squared error method based on an out‐of‐sample technique to evaluate the accuracy of alternative index construction methods.

The introduction of financial products like the property derivatives and home equity insurances to the financial market calls for accurate and robust property price indices. However, the index method and level of temporal aggregation to use still remain unresolved in the index construction literature. This paper contributes to fill these gaps.