IDEAS home Printed from https://ideas.repec.org/a/wly/isacfm/v24y2017i4p138-147.html
   My bibliography  Save this article

Configuring blockchain architectures for transaction information in blockchain consortiums: The case of accounting and supply chain systems

Author

Listed:
  • Daniel E. O'Leary

Abstract

This paper investigates alternative configurations of different blockchain architectures that can be used for gathering and processing transactions in a range of different settings, including accounting, auditing, supply chain and other types of transaction information. Although there has been substantial focus on the peer‐to‐peer and public versions of blockchain, this paper focuses primarily on cloud‐based and private configuration versions of blockchains and investigates use configurations, advantages and limitations as firms bring blockchain‐based market mechanisms into their organizations. In addition, this paper investigates some emerging issues associated with blockchain use in consortium settings. Finally, this paper relates some proposed uses of blockchain for transaction processing to other technologies, such as data warehouses and databases.

Suggested Citation

  • Daniel E. O'Leary, 2017. "Configuring blockchain architectures for transaction information in blockchain consortiums: The case of accounting and supply chain systems," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 24(4), pages 138-147, October.
  • Handle: RePEc:wly:isacfm:v:24:y:2017:i:4:p:138-147
    DOI: 10.1002/isaf.1417
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/isaf.1417
    Download Restriction: no

    File URL: https://libkey.io/10.1002/isaf.1417?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
    ---><---

    References listed on IDEAS

    as
    1. Joyce E. Berg & Thomas A. Rietz, 2003. "Prediction Markets as Decision Support Systems," Information Systems Frontiers, Springer, vol. 5(1), pages 79-93, January.
    2. Geerts, Guido L. & O'Leary, Daniel E., 2015. "A note on an architecture for integrating cloud computing and enterprise systems using REA," International Journal of Accounting Information Systems, Elsevier, vol. 19(C), pages 59-67.
    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. Kopyto, Matthias & Lechler, Sabrina & von der Gracht, Heiko A. & Hartmann, Evi, 2020. "Potentials of blockchain technology in supply chain management: Long-term judgments of an international expert panel," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    2. Dutta, Pankaj & Choi, Tsan-Ming & Somani, Surabhi & Butala, Richa, 2020. "Blockchain technology in supply chain operations: Applications, challenges and research opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).

    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. Marko Corn & Nejc Rov{z}man, 2021. "Unihedge -- A decentralized market prediction platform," Papers 2108.11631, arXiv.org, revised Dec 2021.
    2. Karimi, Majid & Zaerpour, Nima, 2022. "Put your money where your forecast is: Supply chain collaborative forecasting with cost-function-based prediction markets," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1035-1049.
    3. Wolfers, Justin & Zitzewitz, Eric, 2006. "Prediction Markets in Theory and Practice," CEPR Discussion Papers 5578, C.E.P.R. Discussion Papers.
    4. Manski, Charles F., 2006. "Interpreting the predictions of prediction markets," Economics Letters, Elsevier, vol. 91(3), pages 425-429, June.
    5. Mikuláš Gangur & Miroslav Plevný, 2014. "Tools for Consumer Rights Protection in the Prediction of Electronic Virtual Market and Technological Changes," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 16(36), pages 578-578, May.
    6. Urmee Khan & Robert Lieli, 2010. "Information Processing in Prediction Markets: An Empirical Investigation," Working Papers 201426, University of California at Riverside, Department of Economics.
    7. Patrick Buckley & Fergal O’Brien, 0. "The effect of malicious manipulations on prediction market accuracy," Information Systems Frontiers, Springer, vol. 0, pages 1-13.
    8. Khan, Urmee & Lieli, Robert P., 2018. "Information flow between prediction markets, polls and media: Evidence from the 2008 presidential primaries," International Journal of Forecasting, Elsevier, vol. 34(4), pages 696-710.
    9. Victor Tiberius & Christoph Rasche, 2011. "Prognosemärkte," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 21(4), pages 467-472, April.
    10. Ledyard, John & Hanson, Robin & Ishikida, Takashi, 2009. "An experimental test of combinatorial information markets," Journal of Economic Behavior & Organization, Elsevier, vol. 69(2), pages 182-189, February.
    11. Kocsis, David, 2019. "A conceptual foundation of design and implementation research in accounting information systems," International Journal of Accounting Information Systems, Elsevier, vol. 34(C), pages 1-1.
    12. repec:grz:wpsses:2019-01 is not listed on IDEAS
    13. Snowberg, Erik & Wolfers, Justin & Zitzewitz, Eric, 2013. "Prediction Markets for Economic Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 657-687, Elsevier.
    14. Deck, Cary & Hao, Li & Porter, David, 2015. "Do prediction markets aid defenders in a weak-link contest?," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 248-258.
    15. Dilger, Alexander, 2016. "Bedingte Aktiengeschäfte," Discussion Papers of the Institute for Organisational Economics 08/2016, University of Münster, Institute for Organisational Economics.
    16. Bennouri, Moez & Gimpel, Henner & Robert, Jacques, 2011. "Measuring the impact of information aggregation mechanisms: An experimental investigation," Journal of Economic Behavior & Organization, Elsevier, vol. 78(3), pages 302-318, May.
    17. Corgnet, Brice & Deck, Cary & DeSantis, Mark & Porter, David, 2018. "Information (non)aggregation in markets with costly signal acquisition," Journal of Economic Behavior & Organization, Elsevier, vol. 154(C), pages 286-320.
    18. Justin Wolfers & Eric Zitzewitz, 2006. "Five Open Questions About Prediction Markets," NBER Working Papers 12060, National Bureau of Economic Research, Inc.
    19. Ho Cheung Brian Lee & Jan Stallaert & Ming Fan, 2020. "Anomalies in Probability Estimates for Event Forecasting on Prediction Markets," Production and Operations Management, Production and Operations Management Society, vol. 29(9), pages 2077-2095, September.
    20. Patrick Buckley & Fergal O’Brien, 2017. "The effect of malicious manipulations on prediction market accuracy," Information Systems Frontiers, Springer, vol. 19(3), pages 611-623, June.
    21. Johan Perols & Kaushal Chari & Manish Agrawal, 2009. "Information Market-Based Decision Fusion," Management Science, INFORMS, vol. 55(5), pages 827-842, May.

    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:wly:isacfm:v:24:y:2017:i:4:p:138-147. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1099-1174/ .

    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.