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Article: Managing learning and turnover in employee staffing
Title | Managing learning and turnover in employee staffing |
---|---|
Authors | |
Issue Date | 2002 |
Publisher | INFORMS. The Journal's web site is located at http://or.pubs.informs.org |
Citation | Operations Research, 2002, v. 50 n. 6, p. 991-1006 How to Cite? |
Abstract | We study the employee staffing problem in a service organization that uses employee service capacity to meet random, nonstationary service requirements. The employees experience learning and turnover on the job, and we develop a Markov Decision Process (MDP) model which explicitly represents the stochastic nature of these effects. Theoretical results show that the optimal hiring policy is of a state-dependent "hire-up-to" type, similar to an inventory "order-up-to" policy. For two important special cases, a myopic policy is optimal. We also test a linear programming (LP) based heuristic, which uses average learning and turnover behavior, in stationary environments. In most cases, the LP-based policy performs quite well, within 1% of optimality. When flexible capacity-in the form of overtime or outsourcing-is expensive or not available, however, explicit modeling of stochastic learning and turnover effects may improve performance significantly. |
Persistent Identifier | http://hdl.handle.net/10722/157724 |
ISSN | 2023 Impact Factor: 2.2 2023 SCImago Journal Rankings: 2.848 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Gans, N | en_HK |
dc.contributor.author | Zhou, YP | en_HK |
dc.date.accessioned | 2012-08-08T08:55:10Z | - |
dc.date.available | 2012-08-08T08:55:10Z | - |
dc.date.issued | 2002 | en_HK |
dc.identifier.citation | Operations Research, 2002, v. 50 n. 6, p. 991-1006 | en_HK |
dc.identifier.issn | 0030-364X | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/157724 | - |
dc.description.abstract | We study the employee staffing problem in a service organization that uses employee service capacity to meet random, nonstationary service requirements. The employees experience learning and turnover on the job, and we develop a Markov Decision Process (MDP) model which explicitly represents the stochastic nature of these effects. Theoretical results show that the optimal hiring policy is of a state-dependent "hire-up-to" type, similar to an inventory "order-up-to" policy. For two important special cases, a myopic policy is optimal. We also test a linear programming (LP) based heuristic, which uses average learning and turnover behavior, in stationary environments. In most cases, the LP-based policy performs quite well, within 1% of optimality. When flexible capacity-in the form of overtime or outsourcing-is expensive or not available, however, explicit modeling of stochastic learning and turnover effects may improve performance significantly. | en_HK |
dc.language | eng | en_US |
dc.publisher | INFORMS. The Journal's web site is located at http://or.pubs.informs.org | en_HK |
dc.relation.ispartof | Operations Research | en_HK |
dc.title | Managing learning and turnover in employee staffing | en_HK |
dc.type | Article | en_HK |
dc.identifier.email | Zhou, YP: yongpin@hku.hk | en_HK |
dc.identifier.authority | Zhou, YP=rp01614 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.1287/opre.50.6.991.343 | - |
dc.identifier.scopus | eid_2-s2.0-0036878083 | en_HK |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-0036878083&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 50 | en_HK |
dc.identifier.issue | 6 | en_HK |
dc.identifier.spage | 991 | en_HK |
dc.identifier.epage | 1006 | en_HK |
dc.identifier.isi | WOS:000179794700007 | - |
dc.publisher.place | United States | en_HK |
dc.identifier.scopusauthorid | Gans, N=6602173682 | en_HK |
dc.identifier.scopusauthorid | Zhou, YP=9037956000 | en_HK |
dc.identifier.issnl | 0030-364X | - |