IDEAS home Printed from https://ideas.repec.org/a/spr/jlabre/v30y2009i3p245-261.html
   My bibliography  Save this article

Do Arbitrators Use Just Cause Standards in Deciding Discharge and Discipline Cases? A Test

Author

Listed:
  • David Dilts
  • James Moore

Abstract

No abstract is available for this item.

Suggested Citation

  • David Dilts & James Moore, 2009. "Do Arbitrators Use Just Cause Standards in Deciding Discharge and Discipline Cases? A Test," Journal of Labor Research, Springer, vol. 30(3), pages 245-261, September.
  • Handle: RePEc:spr:jlabre:v:30:y:2009:i:3:p:245-261
    DOI: 10.1007/s12122-009-9065-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s12122-009-9065-6
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s12122-009-9065-6?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. Carbonneau, Real & Laframboise, Kevin & Vahidov, Rustam, 2008. "Application of machine learning techniques for supply chain demand forecasting," European Journal of Operational Research, Elsevier, vol. 184(3), pages 1140-1154, February.
    2. Chi Mint Tam & Thomas Tong & K. K. Chan, 2006. "Rough set theory for distilling construction safety measures," Construction Management and Economics, Taylor & Francis Journals, vol. 24(11), pages 1199-1206.
    3. Srinivasan Ragothaman & Bijayananda Naik & Kumoli Ramakrishnan, 2003. "Predicting Corporate Acquisitions: An Application of Uncertain Reasoning Using Rule Induction," Information Systems Frontiers, Springer, vol. 5(4), pages 401-412, December.
    4. Eisenbeis, Robert A, 1977. "Pitfalls in the Application of Discriminant Analysis in Business, Finance, and Economics," Journal of Finance, American Finance Association, vol. 32(3), pages 875-900, June.
    5. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1765, August.
    6. Robert J. Thornton & Perry A. Zirkel, 1990. "The Consistency and Predictability of Grievance Arbitration Awards," ILR Review, Cornell University, ILR School, vol. 43(2), pages 294-307, January.
    7. Geng Cui & Man Leung Wong & Hon-Kwong Lui, 2006. "Machine Learning for Direct Marketing Response Models: Bayesian Networks with Evolutionary Programming," Management Science, INFORMS, vol. 52(4), pages 597-612, April.
    Full references (including those not matched with items on IDEAS)

    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. Chia-Lin Chang & Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2018. "Long Run Returns Predictability and Volatility with Moving Averages," Risks, MDPI, vol. 6(4), pages 1-18, September.
    2. Bell, Peter N, 2013. "New Testing Procedures to Assess Market Efficiency with Trading Rules," MPRA Paper 46701, University Library of Munich, Germany.
    3. Montgomery, D. & Swinnen, G. & Vanhoof, K., 1997. "Comparison of some AI and statistical classification methods for a marketing case," European Journal of Operational Research, Elsevier, vol. 103(2), pages 312-325, December.
    4. Sid Ghoshal & Stephen Roberts, 2016. "Extracting Predictive Information from Heterogeneous Data Streams using Gaussian Processes," Papers 1603.06202, arXiv.org, revised Jul 2018.
    5. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
    6. Shi Yafeng & Tao Xiangxing & Shi Yanlong & Zhu Nenghui & Ying Tingting & Peng Xun, 2020. "Can Technical Indicators Provide Information for Future Volatility: International Evidence," Journal of Systems Science and Information, De Gruyter, vol. 8(1), pages 53-66, February.
    7. Sangho Lee & Youngdoo Son, 2021. "Motor Load Balancing with Roll Force Prediction for a Cold-Rolling Setup with Neural Networks," Mathematics, MDPI, vol. 9(12), pages 1-21, June.
    8. Lin, Hsiou-Wei William & Lo, Huai-Chun & Wu, Ruei-Shian, 2016. "Modeling default prediction with earnings management," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 306-322.
    9. Bohm, Volker & Wenzelburger, Jan, 2005. "On the performance of efficient portfolios," Journal of Economic Dynamics and Control, Elsevier, vol. 29(4), pages 721-740, April.
    10. Stephan Schulmeister, 2000. "Technical Analysis and Exchange Rate Dynamics," WIFO Studies, WIFO, number 25857, March.
    11. Trifan, Emanuela, 2004. "Entscheidungsregeln und ihr Einfluss auf den Aktienkurs," Darmstadt Discussion Papers in Economics 131, Darmstadt University of Technology, Department of Law and Economics.
    12. Adriana Csikosova & Maria Janoskova & Katarina Culkova, 2020. "Application of Discriminant Analysis for Avoiding the Risk of Quarry Operation Failure," JRFM, MDPI, vol. 13(10), pages 1-14, September.
    13. Kun Xing & Honggang Li, 2024. "The profitability of interacting trading strategies from an ecological perspective," Annals of Finance, Springer, vol. 20(3), pages 377-394, September.
    14. Pelau Corina & Barbul Maria, 2021. "Consumers’ perception on the use of cognitive computing," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 15(1), pages 639-649, December.
    15. Erdemlioglu, Deniz & Petitjean, Mikael & Vargas, Nicolas, 2021. "Market instability and technical trading at high frequency: Evidence from NASDAQ stocks," Economic Modelling, Elsevier, vol. 102(C).
    16. Dean Fantazzini & Silvia Figini, 2009. "Random Survival Forests Models for SME Credit Risk Measurement," Methodology and Computing in Applied Probability, Springer, vol. 11(1), pages 29-45, March.
    17. Youssef Zizi & Mohamed Oudgou & Abdeslam El Moudden, 2020. "Determinants and Predictors of SMEs’ Financial Failure: A Logistic Regression Approach," Risks, MDPI, vol. 8(4), pages 1-21, October.
    18. Fischer, Thomas & Riedler, Jesper, 2014. "Prices, debt and market structure in an agent-based model of the financial market," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 95-120.
    19. Sid Ghoshal & Stephen J. Roberts, 2018. "Thresholded ConvNet Ensembles: Neural Networks for Technical Forecasting," Papers 1807.03192, arXiv.org, revised Jul 2018.
    20. Wong, Wing-Keung & Du, Jun & Chong, Terence Tai-Leung, 2005. "Do the technical indicators reward chartists? A study on the stock markets of China, Hong Kong and Taiwan," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 1(2), pages 1-23.

    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:spr:jlabre:v:30:y:2009:i:3:p:245-261. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.