IDEAS home Printed from https://ideas.repec.org/a/taf/uiiexx/v43y2011i8p589-603.html
   My bibliography  Save this article

Cross-training performance in flexible labor scheduling environments

Author

Listed:
  • Fred Easton

Abstract

Cross-training effectively pools multiple demand streams, improving service levels and, when demand streams are negatively correlated, boosting productivity. When services operate for extended hours, however, those benefits are intermittent because employees take their skills home with them at the end of their shift. This study explores how cross-training and workforce management decisions interact to affect labor costs and service levels in extended hour service operations with uncertain demand and employee attendance. Using a two-stage stochastic model, we first optimally staff, cross-train, schedule, and allocate workers across departments. We then simulate demand and attendance and, as needed, re-allocate available cross-trained workers to best satisfy realized demand. Comparing the performance of full- and partial cross-training policies with that of dedicated specialists, we found that cross-training often, but not always, dominated the performance of a specialized workforce. When cross-trained workers are less proficient than specialists, however, increased cross-training forced tradeoffs between workforce size and capacity shortages. However, both workforce size and service levels often improved with increased scheduling flexibility. Further, increased scheduling flexibility appears to be an efficient strategy for mitigating the effects of absenteeism. Thus, scheduling flexibility may be an important cofactor for exploiting the benefits of cross-training in labor scheduling environments.

Suggested Citation

  • Fred Easton, 2011. "Cross-training performance in flexible labor scheduling environments," IISE Transactions, Taylor & Francis Journals, vol. 43(8), pages 589-603.
  • Handle: RePEc:taf:uiiexx:v:43:y:2011:i:8:p:589-603
    DOI: 10.1080/0740817X.2010.550906
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/0740817X.2010.550906
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/0740817X.2010.550906?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.

    Citations

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


    Cited by:

    1. David D. Cho & Kurt M. Bretthauer & Jan Schoenfelder, 2023. "Patient-to-nurse ratios: Balancing quality, nurse turnover, and cost," Health Care Management Science, Springer, vol. 26(4), pages 807-826, December.
    2. Paul, Jomon Aliyas & MacDonald, Leo, 2014. "Modeling the benefits of cross-training to address the nursing shortage," International Journal of Production Economics, Elsevier, vol. 150(C), pages 83-95.
    3. Schoenfelder, Jan & Bretthauer, Kurt M. & Wright, P. Daniel & Coe, Edwin, 2020. "Nurse scheduling with quick-response methods: Improving hospital performance, nurse workload, and patient experience," European Journal of Operational Research, Elsevier, vol. 283(1), pages 390-403.
    4. Perla, Abhinav & Nikolaev, Alexander & Pasiliao, Eduardo, 2018. "Workforce management under social Link Based Corruption," Omega, Elsevier, vol. 78(C), pages 222-236.
    5. Carina Fagefors & Björn Lantz & Peter Rosén, 2020. "Creating Short-Term Volume Flexibility in Healthcare Capacity Management," IJERPH, MDPI, vol. 17(22), pages 1-18, November.
    6. Brusco, Michael J., 2015. "A bicriterion algorithm for the allocation of cross-trained workers based on operational and human resource objectives," European Journal of Operational Research, Elsevier, vol. 247(1), pages 46-59.
    7. Henao, César Augusto & Ferrer, Juan Carlos & Muñoz, Juan Carlos & Vera, Jorge, 2016. "Multiskilling with closed chains in a service industry: A robust optimization approach," International Journal of Production Economics, Elsevier, vol. 179(C), pages 166-178.
    8. Berti, Nicola & Finco, Serena & Battaïa, Olga & Delorme, Xavier, 2021. "Ageing workforce effects in Dual-Resource Constrained job-shop scheduling," International Journal of Production Economics, Elsevier, vol. 237(C).
    9. Gang Li & Joy M. Field & Hongxun Jiang & Tian He & Youming Pang, 2019. "Decision Models for Workforce and Technology Planning in Services," Papers 1909.12829, arXiv.org.

    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:uiiexx:v:43:y:2011:i:8:p:589-603. 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.

    We have no bibliographic references for this item. You can help adding them by using 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/uiie .

    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.