File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1111/poms.13775
- Scopus: eid_2-s2.0-85132891417
- Find via
Supplementary
-
Citations:
- Scopus: 0
- Appears in Collections:
Article: Smart urban transport and logistics: A business analytics perspective
| Title | Smart urban transport and logistics: A business analytics perspective |
|---|---|
| Authors | |
| Keywords | logistics predictive analytics prescriptive analytics smart cities transportation |
| Issue Date | 1-Oct-2022 |
| Publisher | Wiley |
| Citation | Production and Operations Management, 2022, v. 31, n. 10, p. 3771-3787 How to Cite? |
| Abstract | New technologies and innovative business models are leading to connected, shared, autonomous, and electric solutions for the tomorrow of urban transport and logistics (UTL). The efficiency and sustainability of these solutions are greatly empowered by the capability of understanding and utilizing the tremendous amount of data generated by passengers, drivers, and vehicles. In this study, we first review the innovative applications in UTL and several related research areas in the operations management (OM)/operations research (OR) literature. We then highlight the sources, types, and uses of data in different applications. We further elaborate on business analytics techniques and software developed to facilitate the planning and management of UTL systems. Finally, we conclude the paper by reflecting on the emerging trends and potential research directions in data-driven decision making for smart UTL. |
| Persistent Identifier | http://hdl.handle.net/10722/336523 |
| ISSN | 2021 Impact Factor: 4.638 2020 SCImago Journal Rankings: 3.279 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | He, L | - |
| dc.contributor.author | Liu, S | - |
| dc.contributor.author | Shen, ZJM | - |
| dc.date.accessioned | 2024-02-16T03:57:27Z | - |
| dc.date.available | 2024-02-16T03:57:27Z | - |
| dc.date.issued | 2022-10-01 | - |
| dc.identifier.citation | Production and Operations Management, 2022, v. 31, n. 10, p. 3771-3787 | - |
| dc.identifier.issn | 1059-1478 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/336523 | - |
| dc.description.abstract | <p>New technologies and innovative business models are leading to connected, shared, autonomous, and electric solutions for the tomorrow of urban transport and logistics (UTL). The efficiency and sustainability of these solutions are greatly empowered by the capability of understanding and utilizing the tremendous amount of data generated by passengers, drivers, and vehicles. In this study, we first review the innovative applications in UTL and several related research areas in the operations management (OM)/operations research (OR) literature. We then highlight the sources, types, and uses of data in different applications. We further elaborate on business analytics techniques and software developed to facilitate the planning and management of UTL systems. Finally, we conclude the paper by reflecting on the emerging trends and potential research directions in data-driven decision making for smart UTL.</p> | - |
| dc.language | eng | - |
| dc.publisher | Wiley | - |
| dc.relation.ispartof | Production and Operations Management | - |
| dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
| dc.subject | logistics | - |
| dc.subject | predictive analytics | - |
| dc.subject | prescriptive analytics | - |
| dc.subject | smart cities | - |
| dc.subject | transportation | - |
| dc.title | Smart urban transport and logistics: A business analytics perspective | - |
| dc.type | Article | - |
| dc.identifier.doi | 10.1111/poms.13775 | - |
| dc.identifier.scopus | eid_2-s2.0-85132891417 | - |
| dc.identifier.volume | 31 | - |
| dc.identifier.issue | 10 | - |
| dc.identifier.spage | 3771 | - |
| dc.identifier.epage | 3787 | - |
| dc.identifier.eissn | 1937-5956 | - |
| dc.identifier.issnl | 1059-1478 | - |