International comparisons of cost and productivity in construction: a bad example

Best, Rick

doi:10.5130/ajceb.v12i3.2662

Cited by 10 publications

(4 citation statements)

References 1 publication

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“…The BCA study received ridicule from some analysts (e.g. Best, 2012; for ignoring the impact of purchasing power. The original study benchmarked Australian projects against the US Gulf…”

Section: Introductionmentioning

confidence: 99%

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The reliability of currency and purchasing power parity conversion for international project cost benchmarking

Langston

2016

Benchmarking: An International Journal

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Purpose: Project cost is normally a key performance indicator for all projects, and therefore features prominently in benchmarking exercises aimed at identifying best practice. However, projects in different locations first require all costs to be expressed in equivalent units. Failing to do this leads to erroneous and unreliable results. Design/methodology/approach: Applying international construction as the focus for the study, cost data from 23 cities worldwide are compared using a range of methods including currency conversion and purchasing power parity (PPP). Coefficient of variation forms the test for identifying the method with the lowest volatility. Findings: It is found that purchasing power is the preferable theoretical base for international cost conversion, and currency conversion (frequently used by practitioners) is not recommended. The citiBLOC PPP method has the lowest coefficient of variation across the dataset and therefore more closely reflects the Law of One Price that underpins the concept of PPP. Originality/value: This research highlights the importance of a valid cost conversion methodology to properly understand the comparative performance of projects. Its application to benchmarking is demonstrated using the Data Envelopment Analysis (DEA) method.

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“…The BCA study received ridicule from some analysts (e.g. Best, 2012; for ignoring the impact of purchasing power. The original study benchmarked Australian projects against the US Gulf…”

Section: Introductionmentioning

confidence: 99%

“…The BCA study received ridicule from some analysts (e.g. Best, 2012Best, , 2013 for ignoring the impact of purchasing power. The original study benchmarked Australian projects against the US Gulf States where the cost of living was lower than in many other parts of the country, resulting in different levels of domestic purchasing power.…”

Section: Introductionmentioning

confidence: 99%

The reliability of currency and purchasing power parity conversion for international project cost benchmarking

Langston

2016

Benchmarking: An International Journal

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“…Included in their report were data on cost/m 2 for airports, schools, shopping malls and hospitals in both countries obtained from a well-known published cost guide. Apart from the obvious problems of using currency exchange rates and arguably not comparing 'like with like', as pointed out by Best (2012), they selected the US Gulf states as the comparative context to Australia. It can be seen from Table 4 earlier that Houston (Texas) has a much lower citiBLOC index than other US cities.…”

Section: Discussionmentioning

confidence: 99%

The Application of Data Envelopment Analysis to the Benchmarking of Construction Performance in Australian and American High-Rise Buildings

Langston¹

2013

International Journal of Construction Management

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The measurement of construction performance is a vexed problem. Despite much research effort, there remains little agreement over what to measure and how to measure it. The problem is made even more complicated by the desire to benchmark national industry performance against that of other countries. As clearly construction cost forms part of the analysis, the mere adjustment of cost data to an 'international currency' has undermined past attempts to draw any meaningful conclusions. The aim in this paper is to develop a method for benchmarking construction projects on the basis of their integrated time, cost and quality performance, and test it using what is understood to be one of the largest collections of construction project data ever assembled across two sample countries: Australia and the United States. The research draws on 337 high-rise projects of 20 storeys or more, completed between 2003 (i.e. 5 years pre-GFC) and 2012 (i.e. 5 years post-GFC), throughout the five largest cities in Australia and the United States, representing two-thirds of the known population of such buildings in these locations. Performance outputs of construction efficiency and construction complexity are selected to enable projects to be ranked and mapped via data envelopment analysis to identify potential instances of best practice worthy of further investigation. Furthermore, using a four-quadrant model to aid interpretation, it is clear that obtaining best practice in both efficiency (i.e. construction speed) and complexity (i.e. product sophistication) is very challenging and often mutually-exclusive. The use of a four-quadrant model combined with DEA provides context to the analysis. The scales for CE and CC applied in this research render the majority of projects to the 'normal (typical)' quadrant, demonstrating that fast construction speed and high product sophistication are often mutually-exclusive. This is a significant wake-up call for the industry and highlights the marked difference between 'business-asusual' and achieving 'best practice'.

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“…They utilized these figures to infer that Australia is a high cost, low-productivity condition for building infrastructure project. These cases depended on cost / m 2 figures distributed by a noteworthy worldwide construction consultancy (Best, 2012). Watkins et al (2009) classified factors affecting productivity into internal and external factors.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysing Enabling Factors Affecting the On-site Productivity in Indian Construction Industry

Dixit

2018

Period. Polytech. Arch.

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The growth in construction productivity is low and do not continue for a long span of time. The purpose of the present research paper is to analyse the factors affecting on-site construction productivity in Indian construction industry. The tools used for the analysis are reliability analysis to check the consistency of the data, Pearson correlation analysis to mathematically validate the factor analysis, and linear regression analysis to propose a framework of factors affecting construction productivity. The findings of the reliability analysis concludes that the all the factors having a value of more than 0.67, which is considered to be good for the study, and the findings of the study conclude that the most significant 3 attributes grouped in linear regression analysis change in scope (R2), revision in drawings (R15), and response to change orders (R3) having maximum impact over the construction productivity. The research paper attempts to provide an insight and better understanding of the factors affecting on-site construction productivity in India and the ways and means to control and improve construction productivity of construction projects."This paper is the revised version of the paper that has been published in the proceedings of the Creative Construction Conference 2018: Dixit, S., Mandal, S. N., Thanikal, J. V, & Saurabh, K. (2018). Critical Analysis of Factors Affecting the on-site Productivity in Indian Construction Industry, (July), 38–45. https://doi.org/10.3311/CCC2018-006"

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International comparisons of cost and productivity in construction: a bad example

Cited by 10 publications

References 1 publication

The reliability of currency and purchasing power parity conversion for international project cost benchmarking

The reliability of currency and purchasing power parity conversion for international project cost benchmarking

The Application of Data Envelopment Analysis to the Benchmarking of Construction Performance in Australian and American High-Rise Buildings

Analysing Enabling Factors Affecting the On-site Productivity in Indian Construction Industry

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