| dc.contributor.author | Rad, Fakhreddin Fakhrai | |
| dc.contributor.author | Oghazi, Pejvak | |
| dc.contributor.author | Onur, İzmir | |
| dc.contributor.author | Kordestani, Arash | |
| dc.date.accessioned | 2025-03-06T10:25:00Z | |
| dc.date.available | 2025-03-06T10:25:00Z | |
| dc.date.issued | 2025 | en_US |
| dc.identifier.citation | Scopus
EXPORT DATE: 06 March 2025
@ARTICLE{Rad2025,
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85218694648&doi=10.1007%2fs11846-025-00858-1&partnerID=40&md5=dc6a83ca744e185042b31e92394809f6},
affiliations = {School of Social Sciences, Södertörn University, Stockholm, Sweden; School of Management, University of Vaasa, PO Box 700, Vaasa, 65101, Finland; University of Economics and Human Sciences, Warsaw, Poland; Department of Business Administration, Faculty of Economics and Administrative Sciences, Gümüşhane University, Gümüşhane, Türkiye},
correspondence_address = {P. Oghazi; School of Social Sciences, Södertörn University, Stockholm, Sweden; email: Pejvak.oghazi@sh.se},
publisher = {Springer Science and Business Media Deutschland GmbH},
issn = {18636683},
language = {English},
abbrev_source_title = {Rev. Manage. Sci.}
} | en_US |
| dc.identifier.uri | scopus.com/record/display.uri?eid=2-s2.0-85218694648&origin=SingleRecordEmailAlert&dgcid=raven_sc_affil_en_us_email&txGid=8a0ebcbfddff8aab90da1fa677291536 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12440/6417 | |
| dc.description.abstract | This research assesses the adoption of artificial intelligence (AI)-based batch order picking in a warehouse, focusing on benefits, challenges, and critical success factors. Using customer order data and simulation, the study employs a quantitative approach, combining mathematical and statistical estimations with qualitative examinations centered on interviews with the warehouse staff, its Enterprise Resource Planning (ERP) developer, and the AI developer. The findings of this mixed-method study reveal that the AI-based order-picking system (AI-based system) has improved order-picking efficiency by reducing travel distance and time. Nevertheless, challenges hinder maximum utilization of the system. In addition, the research highlights critical success factors and other benefits of adopting the system tailored to warehouse management. Understanding the lessons learned in this research is essential for businesses seeking to adopt AI to enhance their efficiency. © The Author(s) 2025. | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Springer Science and Business Media Deutschland GmbH | en_US |
| dc.relation.ispartof | Review of Managerial Science | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.subject | Artificial intelligence; Benefits; Challenges; Critical success factors; Optimization; Order picking; Warehouse | en_US |
| dc.title | Adoption of AI-based order picking in warehouse: benefits, challenges, and critical success factors | en_US |
| dc.type | article | en_US |
| dc.relation.publicationcategory | Makale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| dc.department | Fakülteler, İktisadi ve İdari Bilimler Fakültesi, İşletme Bölümü | en_US |
| dc.authorid | 0000-0003-3307-9344 | en_US |
| dc.contributor.institutionauthor | İzmir, Onur | |
| dc.identifier.doi | 10.1007/s11846-025-00858-1 | en_US |
| dc.authorwosid | IWV-1124-2023 | en_US |
| dc.authorscopusid | 59647141700 | en_US |
