An input–output analysis of Thailand's construction sector

Three input–output (IO) tables compiled between 1995 and 2000 were used to examine the significance of the construction sector and its relationships with other sectors of the Thai economy. The pull and push effect of the Thai construction sector to the national economy indicated that the former is much larger than the latter. Additionally, the relatively high output multipliers and backward linkage indicators showed that the construction sector had the potential to trigger off production in many economic sectors linked to it. An aggregated sectoral analysis revealed the high dependence of construction on manufacturing followed by services. The findings also suggest that the trends of the profile of inputs and outputs are correlated to the economic conditions in Thailand at the time the IO tables were compiled. Finally, the results of employment analysis showed that although the share of construction sector in direct employment generation may not be very large, its economic importance lies in its direct and indirect contribution to employment through strong backward linkage effects. Consequently, when its backward linkages and output multiplier are considered together with the employment opportunities latent within it, then the construction sector could be a major contributor to the economic growth of Thailand.     

Input–output analysis of the Chinese construction sector

The construction sector has played a key role in the Chinese economy, which has been experiencing a rapid growth for the past two decades. This development and growth are reviewed in a framework of input–output analysis. The national input–output table (IO table) was used to study the current input–output profile of the Chinese construction sector and the relationship between the construction sector and other sectors. The pull and push effect of the Chinese construction industry to the whole national economy has been estimated. It shows that the pull effect is much larger than the push effect. Furthermore, through the analysis of a series of four IO tables spanning over the last 10 years, it reveals that the pull and push effect of the Chinese construction industry are both getting larger and larger. This means the Chinese construction industry is becoming mature and is in great transition.     

Exploring the drivers of firm‐level innovation in the construction industry

A survey of 335 businesses in the Australian road industry has been carried out to ascertain those factors that make firms innovate. ‘Innovative’ is measured by adoption rates of advanced technologies and practices, and the range of innovation drivers reviewed encompasses business strategy and environment. The findings indicate that business strategies are more important than business conditions, and that the following three strategies are significant in differentiating between firms with high and low adoption rates: (1) hiring new graduates; (2) introducing new technologies; and (3) enhancing technical capabilities. The findings also highlight the importance of undertaking R&D and encouraging employee ideas for improvement. The public policy implications are that the quality of university graduates should be protected and advanced, as should technical skills within public sector client agencies.     

Simple Keynesian input–output structural decomposition analysis using weighted Shapley value resolution

This study proposes a method of input–output structural decomposition analysis (I–O SDA) incorporating simple Keynesian modeling and a two-tier KLEM production function framework. The derived model is based on a well-established macro-economic theory and the well-accepted production function form, which presupposes that I–O SDA not only compares I–O table coefficients but also employs well established economic theory. Additionally, weighted Shapley value is introduced to construct a generalized equation for deriving a set of I–O SDA solutions and to verify that, because this set of solutions satisfies efficiency and aggregation axioms, arbitrary use of ad hoc decomposition forms can be avoided, and residuals can be eliminated. The authors would like to thank the National Science Council of the Republic of China, Taiwan, for financially supporting this research under Contract No. NSC 94-2415-H-006-009.     

Input–output analysis of Irish construction sector greenhouse gas emissions

Ireland is committed to limiting its greenhouse gas (GHG) emissions to 113% of 1990 levels over the period 2008–12 and to 84% of 2005 levels by 2020 under the Kyoto Agreement and the EU's 2020 target by 2020 respectively. National policies have targeted many industry sectors but have failed to directly tackle GHG emissions associated with construction activity. This paper estimates energy and GHG emissions intensities of the Irish construction sector and subsectors and estimates its contribution to Irish national emissions. This information is used to identify and assess the impacts of policy measures which would result in a reduction in emissions from the sector in a cost-effective manner. Energy and emissions intensities are estimated using input–output analysis techniques applied to Irish construction sector.     

A study on the building of a new “output–output model” and its usefulness: based on a comparative analysis of the input–output model

This paper describes the building of a new open static “output–output” (O–O) model in comparison to the open static input–ouput (I–O) model developed by Leontief (Rev Econ Stat 18:105–125, 1936). While the I–O model can be characterized as a system that relates final demand to gross output, the O–O model relates gross output for final demand (endogenous or exogenous) to gross output for output (endogenous). We perform a comparative analysis between the two models in structure and characteristics and illustrate the usefulness of the O–O model, for example, by formulating I–O multipliers that can accept output as an initial change. The comprehensive analysis conducted in this paper, including a numerical illustration with an example, shows that the two models form a mutually supplementary relationship and could give rise to a fundamental framework for the analyses of various regional and national economic activities.     

Input structure of the construction industry: a cross‐country analysis, 1968–90

During the past several decades, globalization has led to the integration of product markets. Rapid increases in cross‐border economic, social, technological and cultural exchange have become the key elements of knowledge diffusion and thus technology spillovers among countries. As a result, the debate as to whether absolute convergence occurs at the cross‐country level has increasingly attracted the attention of researchers. The aim of this study is to examine the changes in the input structure of the construction industry in nine developed countries between the late 1960s and 1990 and to evaluate whether convergence occurs at input industry level. The analysis of the technical coefficients for 35 industries reveals that, across countries and over time, not only the key inputs but also the new high and low input industries are similar. The estimation of variance factors on the other hand suggests that (1) during the sample period, the input structure of the industry is dominated by divergence rather than convergence; (2) among the input industries, services in particular tend for convergence; and (3) manufacturing inputs provide a mixed picture where only a few inputs show convergence and the remaining inputs show in general weak divergence.     

Uncertainty quantification of structural flexibility identified from input–output measurement data for reliability analysis

In contrast to the traditional uncertainty quantification of the modal parameters identified from the output-only measurement data, this study develops an uncertainty propagation and quantification method for structural flexibility identified from input–output measurement data and then uses the derived flexibility matrix for structural reliability analysis. First, a novel procedure for variance estimations of the complete system matrix of the state-space model is derived based on first-order perturbation theory. Then, the mode scaling factors and integrated modal flexibility are subsequently derived and quantified. Finally, the predicted displacements and their uncertainty intervals are used to implement the reliability analysis in terms of the structural displacement serviceability limit state (SLS). The accuracies of the derived expressions are verified by a numerical example through the comparison of variance values estimated from Monte Carlo simulations. The simulation example also indicates that we can expect to identify structural parameters with higher reliability if the input force to the structure is measured, and the identified modal scaling and corresponding flexibility matrix undergo more uncertainty than those of the modal parameters. Finally, we apply the proposed uncertainty quantification method to a scaled three-story frame structure to demonstrate its practicability. The proposed method bridges a gap between the identified structural flexibility and structural reliability analysis directly by the probability category.     

Stochastic key sector analysis: an application to a regional input–output framework

Limits on the precision of technical relationships within input–output frameworks have led to the use of stochastic analytical methods. The notion of stochastic analysis is developed in this paper to discern how the inherent imprecision effect, when aggregated data are utilised, affects the concomitant key sector analysis. Through a Monte Carlo based simulation, the stochastic key sector graph is introduced, with numerical expressions defined which quantify the association of the individual sectors to quadrants of the graph. The technical developments are benchmarked on a small problem, before a stochastic key sector analysis on an aggregated regional input–output table is reported. Comparisons are made between results when the aggregation of sectors is not employed. The paper reveals that aggregation in key sector analysis is inevitably a poor idea. However, it is argued that aggregation is often a practical necessity, so quantifying the uncertainty that is attendant on this aggregation is important, with the “association” expressions introduced potentially central to elucidate this uncertainty. The conclusions of this paper suggest that where analysts and decision makers are obliged to aggregate tables for analytical purposes then problems might be mitigated where marginal sectors are treated with care.     

A review of studies on Public–Private Partnership projects in the construction industry

Public–Private Partnership (PPP) in construction is gaining in popularity. Although papers published in major journals have documented real cases of PPP projects, there appears to be a lack of systematically summarizing what they have already provided. Consequently, this paper reviewed PPP studies published in the six top journals in the construction field. The objectives are to compare and contrast the findings of the studies so as to provide insights for directing further PPP research and improving the existing practices of PPP projects. To achieve the review objectives, studies were first classified as either empirical or non-empirical. Empirical studies were further grouped under three themes: risks, relationships, and financing. Non-empirical studies were grouped under five themes: financing, project success factors, risks, and concession period. Suggestions for further research are risks, financing, contractual agreements, development of PPP models, concession periods, and strategies in choosing the right type of PPP.     

The impact of immigration on interregional migrations: an input–output analysis with an application for Spain

Developed countries in general, Spain in particular, have experienced a dramatic rise in the reception of foreign workers in the last decade. Among all the economic and social effects originated by the arrivals of immigrants, the literature has paid some attention to the potential effect that this immigration can produce on the internal migration patterns (the so-called “displacement effect”). This paper proposes the use of a multi-region input–output model of migrations for measuring how the reception of immigrants in one region displaces population among all the regions included in the model. From some basic assumptions, the input–output methodology proposed describes how the arrival of one immigrant in one region i, by the dissemination of internal population from i, generates indirect effects on other region j. To illustrate the methodology proposed in the paper, an empirical application for Spain is also included.     

An empirical analysis of the influences of corporate social responsibility on organizational performance of Taiwan’s construction industry: using corporate image as a mediator

Corporate social responsibility (CSR) has become a hot issue for modern enterprises recently. The primary purpose of this study was to investigate the relationships of CSR and organizational performance. The secondary purpose was to determine whether the effect of CSR on organizational performance could be mediated by corporate image. To fulfil the primary purpose, a questionnaire-based survey was used to measure CSR, corporate image and overall organizational performance in Taiwan’s construction industry. Two hundred and eighty-one valid samples were collected and statistically analysed using factor analysis, correlation analysis and hierarchical regression analysis. The analysis results suggest that CSR is positively correlated with corporate image and organizational performance. Additionally, levels of corporate image are positively associated with organizational performance levels. The results also indicate that corporate image may serve as a mediator between CSR and organizational performance, meaning that companies benefit from investment in CSR realization, even if they also have a positive corporate image.     

Market structure of China’s construction industry based on the Panzar–Rosse model

The structure–conduct–performance (SCP) paradigm posits that market structure determines market performance, and the generally low productivity of China’s construction industry is a reflection of the irrationality of its market structure. Currently, the main approaches for measuring market structure can be classified as either structural approaches or non-structural approaches. Because the statistical data on structural approaches is one-sided, the indicators for the Panzar–Rosse model (a non-structural approach) for the construction industry can be selected by examining the Panzar–Rosse model and comparing the characteristics of the construction industry with those of the banking industry. The Panzar–Rosse model is employed to assess the market structure of 21 listed companies in China’s construction industry during the period from 2009 to 2011. The analysis revealed that China’s construction industry operates under conditions of monopolistic competition with free-entry equilibrium. The methods and results of the research are expected to contribute to the advancement of theories related to and methods of analysing the market structure of industries other than the banking industry.     

Integrating the fragmented regional and subregional socioeconomic forecasting and analysis: a spatial regional econometric input–output framework

This study presents an integrated socioeconomic forecasting and analysis framework: a spatial regional econometric input?Coutput model and its application to the Chicago metropolitan area. The new framework is designed to overcome some limitations of existing models, particularly (1) limited consideration of population?Cemployment interactions and (2) dominance of top-down approach to vertical integration of regional and subregional variables. It captures local and lower level conditions and their effects on macroeconomic variables by using a modified disequilibrium adjustment model that incorporates subregional dynamics into a regional econometric input?Coutput model in a reciprocal, interactive manner, as opposed to a top-down allocation process. The framework also considers both region-wide and subregional level population?Cemployment interactions more systematically. It is demonstrated that the present model can support socioeconomic forecasting and a broad range of analyses, including the examinations of the macroeconomic impacts of local actions.     

Negatives in symmetric input–output tables: the impossible quest for the Holy Grail

In the Supply-Use (or Make-Use) input–output models, “product-technology” (PT) or “fixed-industry-sales-structure” (FISS) assumptions are more widely adopted (SNA, Eurostat) for deriving symmetric input–output tables (SIOT) than “industry-technology” or “fixed-product-sales-structure” assumptions, but generate negatives in the SIOT. A SIOT deduced from the Supply-Use model is considered as satisfactory as soon as it contains no more negatives; scholars have focused on the negatives in the SIOT and on how to remove them. However, as a SIOT may include no negatives even if there are some negatives in the inverse Supply matrix, we have completely reversed the reasoning. A counter-example demonstrates that computing the inverse Supply matrix, as imposed by PT or FISS assumptions, is mathematically a nonsense operation even when the symmetric input–output tables do not include any negative; this result is new. Hence, deriving a SIOT under PT or FISS assumption must be rejected. Three applications are provided: Austria 2000 and 2005 and USA 2007.     

The multidimensional nD-GRAS method: Applications for the projection of multiregional input–output frameworks and valuation matrices

We present a multidimensional generalization of the GRAS method (nD-GRAS) for the estimation of multiple matrices in an integrated framework. The potential applications of this method in regional and multi-regional input–output analyses based on national/regional accounts frameworks are many. We provide two real applications, a 3D-GRAS that estimates a use table at basic prices jointly with valuation matrices for Denmark; and a 4D-GRAS for estimating intercountry input–output tables with OECD data. We show that higher dimensional GRAS methods provide more consistent and accurate estimates than those with lower number of dimensions. We provide the analytical closed-form solution and the RAS-like algorithm for an easy operationalization.     

Applications of additive manufacturing in the construction industry – A forward-looking review

Additive manufacturing (AM), also known as 3D printing, fabricates components in a layerwise fashion directly from a digital file. Many of the early applications of AM technologies have been in the aerospace, automotive, and healthcare industries. Building on the advances in AM in these industries, there are several experimental applications of AM in the construction sector. Early investigations suggest that use of AM technologies for construction have the potential to decrease labor costs, reduce material waste, and create customized complex geometries that are difficult to achieve using conventional construction techniques. However, these initial investigations do not cover the full range of potential applications for construction or exploit the rapidly maturing AM technologies for a variety of material types. This paper provides an up-to-date review of AM as it relates to the construction industry, identifies the trend of AM processes and materials being used, and discusses related methods of implementing AM and potential advancements in applications of AM. Examples of potential advancements include use of multi-materials (e.g., use of high-performance materials only in areas where they are needed), in-situ repair in locations that are difficult or dangerous for humans to access, disaster relief construction in areas with limited construction workforce and material resources, structural and non-structural elements with optimized topologies, and customized parts of high value. AM's future in the construction industry is promising, but interdisciplinary research is still needed to provide new materials, new processes, faster printing, quality assurance, and data on mechanical properties before AM can realize its full potential in infrastructure construction.     

Impact of pre‐construction planning and project characteristics on performance in the US electrical construction industry

The mild recession experienced in the early part of this decade forced many US electrical contractors to reduce their profit margins as a way to win jobs and survive economically. However, to make up for lower profit margins, contractors turned to ‘better planning’ as a method for improving their efficiency and increasing their profitability. In general, contractors believe that better planning contributes to better project performance, but the evidence has been mostly anecdotal. A study was conducted recently that transformed anecdotal evidence about the impact of pre‐construction planning on performance into quantitative evidence. The research resulted in the development of a model pre‐construction planning process that was based on outstanding projects that were well planned and performed well. The study quantified the relationship between pre‐construction planning activities, project characteristics and performance, and a separate validation study found that those projects that performed a comprehensive planning process similar to the model planning process were more likely to achieve their estimated work hours, profit, budget and completion goals.     

Analysis of the causality links between the growth of the construction industry and the growth of the macro‐economy in Ghana

A vibrant construction industry in a developing country, that mobilizes human and local material resources in the development and maintenance of buildings, housing and physical infrastructure, is an important means to promote increased local employment and accelerate economic growth. Ghana, a country of about 22 million people, currently has one of the fastest growing economies in West Africa. The Government of Ghana (GOG) has recently set a target of annual economic growth rate of 8% and above, up from annual growth rates of 5–6% in the past five years (2001–05). It intends to use the agricultural sector as the major vehicle for achieving such high growth rates in order for the country to reach the status of a middle income country by 2015. Surprisingly, the construction industry was left out from the list of major growth drivers of the economy. We contend that with the construction industry currently making up the third largest sector of the economy, special attention should be given to this industry as one of the main drivers of economic growth in Ghana. Therefore we conducted a study to analyse the causality links between the growth in the construction industry and the growth in the macro‐economy of Ghana, measured by the gross domestic product (GDP), to ascertain whether the construction industry can be used to lead the entire economy on a growth path. The analysis was based on a simple Granger causality test using time series data from 1968 to 2004. We showed that growth in the construction industry Granger‐caused growth in GDP, with a three‐year lag. The construction industry needs to be considered as one of the major drivers of economic growth in Ghana.