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dc.title | Assessing the factors impacting shipping container dwell time: A multi-port optimization study | en |
dc.contributor.author | Saini, Mohan | |
dc.contributor.author | Lerher, Tone | |
dc.relation.ispartof | Business: Theory and Practice | |
dc.identifier.issn | 1648-0627 Scopus Sources, Sherpa/RoMEO, JCR | |
dc.date.issued | 2024 | |
utb.relation.volume | 25 | |
utb.relation.issue | 1 | |
dc.citation.spage | 51 | |
dc.citation.epage | 60 | |
dc.type | article | |
dc.language.iso | en | |
dc.publisher | Vilnius Gediminas Technical University | |
dc.identifier.doi | 10.3846/btp.2024.19205 | |
dc.relation.uri | https://journals.vilniustech.lt/index.php/BTP/article/view/19205 | |
dc.relation.uri | https://journals.vilniustech.lt/index.php/BTP/article/view/19205/12115 | |
dc.subject | container | en |
dc.subject | dwell time | en |
dc.subject | ocean port | en |
dc.subject | optimization | en |
dc.subject | port performance | en |
dc.subject | shipping | en |
dc.description.abstract | Ocean transportation is the most preferred mode of transportation that represents a significant role in the global trade. Ocean transportation comprises around 80% of the aggregate worldwide cargo volume. This research paper focused on evaluating the factors that influence the dwell time of the shipping containers. Dwell time is one of the important port performance parameters which evaluates the time spent by the container in a port. In this research, the data from the fourteen major ports was collected and analysed across the variables, such as cycle, size, mode, status, delivery and tracking technology for evaluating the variation in container dwell time. OLS regression method (Ordinary least squares) along with independent sample T test was adopted for the analysis of 2.8 million container data entries utilizing python for big data analysis and SPSS. For the top three ports with lowest RMSE (Root mean square error), Port A – 15.6 %, Port G – 15.7 % and Port L – 15.86 %, a qualitative study was performed to identify the reasons for the variation in dwell time. The major reasons identified included free days period, trans-shipment port, high rail frequency, industrial hubs in the vicinity of the ports for lower dwell time. A qualitative research framework was presented as the research outcomes and reasons for variations in a multiport study. | en |
utb.faculty | Faculty of Management and Economics | |
dc.identifier.uri | http://hdl.handle.net/10563/1011917 | |
utb.identifier.scopus | 2-s2.0-85184903611 | |
utb.source | j-scopus | |
dc.date.accessioned | 2024-03-05T08:38:52Z | |
dc.date.available | 2024-03-05T08:38:52Z | |
dc.description.sponsorship | FaME TBU, (IGA/FaME/2022/005) | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.rights.access | openAccess | |
utb.ou | Department of Industrial Engineering and Information Systems | |
utb.contributor.internalauthor | Saini, Mohan | |
utb.fulltext.affiliation | Mohan SAINI 1, 2, Tone LERHER 3 1 Department of Industrial Engineering and Information Systems, Faculty of Management and Economics, Tomas Bata University in Zlin, Czech Republic 2 School of Management and Commerce, Dev Bhoomi Uttarakhand University, Dehradun, Uttarakhand, India 3 Faculty of Logistics, Laboratory for Cognitive Systems in Logistics, University of Maribor, Celje, Slovenia | |
utb.fulltext.dates | received 22 May 2023 accepted 29 November 2023 | |
utb.fulltext.sponsorship | The authors would like to thank the Internal Grant Agency of FaME TBU in Zlín No. IGA/FaME/2022/005 for providing financial support. | |
utb.scopus.affiliation | Department of Industrial Engineering and Information Systems, Faculty of Management and Economics, Tomas Bata University in Zlin, Czech Republic; School of Management and Commerce, Dev Bhoomi Uttarakhand University, Uttarakhand, Dehradun, India; Faculty of Logistics, Laboratory for Cognitive Systems in Logistics, University of Maribor, Celje, Slovenia | |
utb.fulltext.projects | IGA/FaME/2022/005 | |
utb.fulltext.faculty | Faculty of Management and Economics | |
utb.fulltext.ou | Department of Industrial Engineering and Information Systems |