Parametric estimation of supplier's plant construction costs
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F22%3A43921917" target="_blank" >RIV/62156489:43110/22:43921917 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.52514/sier.v1i2.19" target="_blank" >https://doi.org/10.52514/sier.v1i2.19</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.52514/sier.v1i2.19" target="_blank" >10.52514/sier.v1i2.19</a>
Alternative languages
Result language
angličtina
Original language name
Parametric estimation of supplier's plant construction costs
Original language description
Cost engineers of buying enterprises perform detailed product cost calculations of externally manufactured components. The aim of these calculations is to determine what a product should cost and to support purchasing functions in fact-based negotiations. While product cost engineers have deep knowledge in the calculation of direct cost, they need support in the calculation of supplier's indirect cost categories. The calculation of industrial rent, which is expressed in annual cost per m2 of occupied plant building floor space can be improved by providing accurate construction cost estimates. Construction costs are strongly impacting the calculation of supplier's annual building depreciation, which is a crucial cost driver for the determination of the industrial rent. Academic literature is actually not providing an accurate and suitable cost model for product cost engineers, which is estimating construction cost per m2 depending on different industrial building categories and alternative supplier plant locations. The paper aims to close this gap by applying linear regression analysis on a set of European construction cost data considering two industrial building categories: "warehouses/basic factory units" and "high-tech factories". By regressing construction cost against construction labor rates within different supplier plant locations it was possible to form suitable and accurate parametric regression functions with R2 values between 0.74 and 0.88. Next to high R2 values acceptable mean average percentage errors between 7.45% and 11.77% could be realized by comparing estimated with observed construction cost. The estimation of industrial construction costs based on the paper's results can be used to improve the calculation of industrial rent, which is one cost element, that has to be covered within product cost engineer's Should Cost Calculations.
Czech name
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Czech description
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Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
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OECD FORD branch
50202 - Applied Economics, Econometrics
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
SCENTIA International Economic Review
ISSN
2748-0089
e-ISSN
2748-0089
Volume of the periodical
1
Issue of the periodical within the volume
2
Country of publishing house
DE - GERMANY
Number of pages
27
Pages from-to
95-121
UT code for WoS article
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EID of the result in the Scopus database
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