File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1111/poms.12888
- Scopus: eid_2-s2.0-85059595174
- WOS: WOS:000455019100002
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Call Center Arrivals: When to Jointly Forecast Multiple Streams?
Title | Call Center Arrivals: When to Jointly Forecast Multiple Streams? |
---|---|
Authors | |
Keywords | arrival process lag dependence vector time series workforce management |
Issue Date | 2019 |
Publisher | Wiley-Blackwell Publishing, Inc.. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1937-5956 |
Citation | Production and Operations Management, 2019, v. 28 n. 1, p. 27-42 How to Cite? |
Abstract | We consider call centers that have multiple (potentially inter‐dependent) demand arrival streams. Workforce management of such labor intensive service systems starts with forecasting future arrival demand. We investigate the question of whether and when to jointly forecast future arrivals of the multiple streams. We first develop a general statistical model to simultaneously forecast multi‐stream arrival rates. The model takes into account three types of inter‐stream dependence. We then show with analytical and simulation studies how the forecasting benefits of the multi‐stream forecasting model vary by the type, direction, and strength of inter‐stream dependence. In particular, we find that it is beneficial to simultaneously forecast multi‐stream arrivals (instead of separately forecasting each stream), when there exists inter‐stream lag dependence among daily arrival rates. Empirical studies, using two real call center datasets further demonstrate our findings, and provide operational insights into how one chooses forecasting models for multi‐stream arrivals. |
Persistent Identifier | http://hdl.handle.net/10722/284773 |
ISSN | 2023 Impact Factor: 4.8 2023 SCImago Journal Rankings: 3.035 |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ye, H | - |
dc.contributor.author | Luedtke, J | - |
dc.contributor.author | Shen, H | - |
dc.date.accessioned | 2020-08-07T09:02:26Z | - |
dc.date.available | 2020-08-07T09:02:26Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Production and Operations Management, 2019, v. 28 n. 1, p. 27-42 | - |
dc.identifier.issn | 1059-1478 | - |
dc.identifier.uri | http://hdl.handle.net/10722/284773 | - |
dc.description.abstract | We consider call centers that have multiple (potentially inter‐dependent) demand arrival streams. Workforce management of such labor intensive service systems starts with forecasting future arrival demand. We investigate the question of whether and when to jointly forecast future arrivals of the multiple streams. We first develop a general statistical model to simultaneously forecast multi‐stream arrival rates. The model takes into account three types of inter‐stream dependence. We then show with analytical and simulation studies how the forecasting benefits of the multi‐stream forecasting model vary by the type, direction, and strength of inter‐stream dependence. In particular, we find that it is beneficial to simultaneously forecast multi‐stream arrivals (instead of separately forecasting each stream), when there exists inter‐stream lag dependence among daily arrival rates. Empirical studies, using two real call center datasets further demonstrate our findings, and provide operational insights into how one chooses forecasting models for multi‐stream arrivals. | - |
dc.language | eng | - |
dc.publisher | Wiley-Blackwell Publishing, Inc.. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1937-5956 | - |
dc.relation.ispartof | Production and Operations Management | - |
dc.rights | Preprint This is the pre-peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. Postprint This is the peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. | - |
dc.subject | arrival process | - |
dc.subject | lag dependence | - |
dc.subject | vector time series | - |
dc.subject | workforce management | - |
dc.title | Call Center Arrivals: When to Jointly Forecast Multiple Streams? | - |
dc.type | Article | - |
dc.identifier.email | Shen, H: haipeng@hku.hk | - |
dc.identifier.authority | Shen, H=rp02082 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1111/poms.12888 | - |
dc.identifier.scopus | eid_2-s2.0-85059595174 | - |
dc.identifier.hkuros | 312351 | - |
dc.identifier.volume | 28 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 27 | - |
dc.identifier.epage | 42 | - |
dc.identifier.isi | WOS:000455019100002 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 1059-1478 | - |