Author
Listed:
- Emanuel Stocker
- Tobias Schrag
Abstract
Purpose - The concept about life cycle costing (LCC) as a part of life cycle management is commonly of international interest. To calculate LCC in the early stage available data, which has been adjusted for the forecasting is necessary. The main problem therefore is the choice and to index the data. This paper include the evaluation of specific values of operating costs (benchmarks). It reviews already existing and published data from different benchmarking reports, which are already aggregated. Research questions - Is there a correlation refer to the life time and the inflation? - Where are uniform and different effects of the trends? - What is the min./max. deviation for random chosen data of each cost category? Design/methodology/approach The study put the focus on published reports of operating cost of office buildings in Germany, Austria and Switzerland. The review is about 7 different public reports over different time periods. Altogether there are about 35 reports. The reports have different cost categories, space definitions and definitions of quality levels, which have to be considered. For the prediction of life cycle cost the benchmarks are usually adjusted by the inflation. Therefore an example with predicted data from 2000 to 2010 and will show the difference between each adjustment. Findings - The evaluation is made for each cost categories. First results shows relevant differences on same specific values. According to the data of the chosen report the total cost will change immediately. One reason therefore is the different structure of the survey. But within factors the different data could be compared. The result at the end are different indexes of the predicted operating cost.
Suggested Citation
Emanuel Stocker & Tobias Schrag, 2012.
"Using benchmarks to predict life cycle cost?,"
ERES
eres2012_273, European Real Estate Society (ERES).
Handle:
RePEc:arz:wpaper:eres2012_273
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More about this item
JEL classification:
- R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location
Statistics
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