IDEAS home Printed from https://ideas.repec.org/a/taf/conmgt/v30y2012i1p81-92.html
   My bibliography  Save this article

An overview of component unit pricing theory

Author

Listed:
  • David William Cattell

Abstract

Component unit pricing (CUP) theory presents a fresh approach to item pricing, described as the process of distributing the overall price among its constituent component items. This theory provides explanation and proof that different distributions of mark-up among the items of a project produce different levels of reward for contractors, while exposing them to different degrees of risk. The theory describes the three identified sources of these rewards, namely those of improved cash flow, escalation in compensation and valuations of likely variations. In addition, it also provides the first explanation of the three risks involved, namely the risk of ‘rejection’, the risk of ‘reaction’ and the risk of ‘being wrong’. In combination, it provides a means by which both the rewards as well as these risks can now be measured given any pricing scenario. This theory gives effect to fuzzy constraints on the price of each item, providing a scientific basis by which to identify more extreme prices when pursuing more profit and more restrained prices when seeking to reduce risk. Overall, it provides a basis by which to moderate these two objectives in the pursuit of the maximization of a contractor’s utility. A test on a hypothetical project indicates an improvement of more than 150% on utility, if a contractor applies this theory, compared to the position when balanced prices are used instead.

Suggested Citation

  • David William Cattell, 2012. "An overview of component unit pricing theory," Construction Management and Economics, Taylor & Francis Journals, vol. 30(1), pages 81-92, December.
    • Handle: RePEc:taf:conmgt:v:30:y:2012:i:1:p:81-92
    DOI: 10.1080/01446193.2011.648948
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01446193.2011.648948
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/01446193.2011.648948?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Engle, Robert F. & Manganelli, Simone, 2001. "Value at risk models in finance," Working Paper Series 75, European Central Bank.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Polat Gul & Turkoglu Harun & Damci Atilla & Akin Firat Dogu, 2020. "Detecting unbalanced bids via an improved grading-based model," Organization, Technology and Management in Construction, Sciendo, vol. 12(1), pages 2072-2082, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hassan Belkacem Ghassan & Abdelkrim Ahmed Guendouz, 2019. "Panel modeling of z-score: evidence from Islamic and conventional Saudi banks," International Journal of Islamic and Middle Eastern Finance and Management, Emerald Group Publishing Limited, vol. 12(3), pages 448-468, July.
    2. Enrico Zaninotto & Alessandro Rossi & Loris Gaio, 1999. "Stochastic learning in coordination games: a simulation approach," Quaderni DISA 015, Department of Computer and Management Sciences, University of Trento, Italy, revised 29 Jun 2003.
    3. Gonzalo Cortazar & Alejandro Bernales & Diether Beuermann, 2005. "Methodology and Implementation of Value-at-Risk Measures in Emerging Fixed-Income Markets with Infrequent Trading," Finance 0512030, University Library of Munich, Germany.
    4. Buczyński Mateusz & Chlebus Marcin, 2018. "Comparison of Semi-Parametric and Benchmark Value-At-Risk Models in Several Time Periods with Different Volatility Levels," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 14(2), pages 67-82, June.
    5. Zapodeanu Daniela & Cociuba Mihai & Petria Nicolae, 2012. "The Role Of Value At Risk In The Management Of Asset And Liabilities," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(2), pages 635-640, December.
    6. James M. O'Brien & Pawel J. Szerszen, 2014. "An Evaluation of Bank VaR Measures for Market Risk During and Before the Financial Crisis," Finance and Economics Discussion Series 2014-21, Board of Governors of the Federal Reserve System (U.S.).
    7. Bakshi, Gurdip & Panayotov, George, 2010. "First-passage probability, jump models, and intra-horizon risk," Journal of Financial Economics, Elsevier, vol. 95(1), pages 20-40, January.
    8. Carol Alexander & Emese Lazar & Silvia Stanescu, 2011. "Analytic Approximations to GARCH Aggregated Returns Distributions with Applications to VaR and ETL," ICMA Centre Discussion Papers in Finance icma-dp2011-08, Henley Business School, University of Reading.
    9. Hassan Belkacem GHASSAN, 2017. "New alternative measuring financial stability," Turkish Economic Review, KSP Journals, vol. 4(3), pages 275-281, September.
    10. Alejandro Bernales & Diether W. Beuermann & Gonzalo Cortazar, 2014. "Thinly traded securities and risk management," Estudios de Economia, University of Chile, Department of Economics, vol. 41(1 Year 20), pages 5-48, June.
    11. O’Brien, James & Szerszeń, Paweł J., 2017. "An evaluation of bank measures for market risk before, during and after the financial crisis," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 215-234.
    12. Dr. Kyriazopoulos Georgios & Dr. Drympetas Evaggelos & Kollias Konstantinos, 2020. "Risk Management after Mergers and Acquisitions. Evidence from the Greek Banking System," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 10(3), pages 1-5.
    13. Allen, David E. & McAleer, Michael & Powell, Robert J. & Singh, Abhay K., 2017. "Volatility Spillovers from Australia's major trading partners across the GFC," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 159-175.
    14. Marios Nerouppos & David Saunders & Costas Xiouros & Stavros A. Zenios, 2006. "Risk Management in Emerging Markets: Practical Methodologies and Empirical Tests," Multinational Finance Journal, Multinational Finance Journal, vol. 10(3-4), pages 179-221, September.
    15. Giannis Vardas & Anastasios Xepapadeas, 2006. "Preserving Biodiversity: Ambiguity and Safety Rules," Working Papers 0607, University of Crete, Department of Economics.
    16. Claudeci Da Silva & Hugo Agudelo Murillo & Joaquim Miguel Couto, 2014. "Early Warning Systems: Análise De Ummodelo Probit De Contágio De Crise Dos Estados Unidos Para O Brasil(2000-2010)," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 110, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    17. Sharif Mozumder & Arafatur Rahman, 2016. "Market Risk Of Investment In Us Subprime Crisis: Comparison Of A Pure Diffusion And A Pure Jump Model," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(03), pages 1-17, September.
    18. Szego, Giorgio, 2005. "Measures of risk," European Journal of Operational Research, Elsevier, vol. 163(1), pages 5-19, May.
    19. Sabrina Khanniche, 2009. "Evaluation of Hedge Fund Returns Value at Risk Using GARCH Models," EconomiX Working Papers 2009-46, University of Paris Nanterre, EconomiX.
    20. Rossignolo, Adrian F. & Fethi, Meryem Duygun & Shaban, Mohamed, 2012. "Value-at-Risk models and Basel capital charges," Journal of Financial Stability, Elsevier, vol. 8(4), pages 303-319.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:conmgt:v:30:y:2012:i:1:p:81-92. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RCME20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.