|dc.description.abstract||This Thesis describes an approach to the development and testing of a model that can
compare construction performance across time, space, and economic system. Labour
and capital productivity measures as well as the multi-factor approach were evaluated.
Capital productivity alone, as a 'pure' financial ratio, appears able to deal with the key
problems posed by indexation, to deal with inflation for time-series comparisons, and
fluctuating currency exchange rates, for international comparisons.
The major flaws with traditional capital productivity measures, particularly the problems
inherent in valuing the 'capital' employed in a given industry or sector, are discussed and
the model is developed to meet the objections. The notion of capital productivity
employed in the model, while in computational terms similar to the traditional approach,
is different in philosophical terms. Thus instead of than attempting to 'value' the capital
employed in the productive process, the cost of capital 'sunk' is valued making allowance
for notional depreciation based on the balance of the different types of assets employed.
The discount rate emerges by counterpoising the discounted value of anticipated future
profits against the historic cost of investment sunk into the current stock of capital goods.
There are problems specific to construction, in particular the incidence of off-site
prefabrication and plant hire, which tend to make traditional capital productivity largely
irrelevant to the construction process. An input-output framework is used to examine the
productivity involved in the total building process as opposed to the on-site activities. In
addition, the problems of incompatibility across economic systems manifested in such
issues as differential rates of indirect taxation etc., is allowed for by adjusting the price
levels from market prices to 'eigenprices' an input-output based approach.
The resulting model is tested via an inter-industry time-series Case Study of the UK over
the period 1948 to 1990 using six broad industrial groupings. The strengths and
weaknesses of the approach are discussed in the light of the Case Study results.||