Modeling Shipment Spot Pricing in the Australian Container Shipping Industry: Case of ASIA-OCEANIA trade lane.

Ubaid, A; Hussain, F; Charles, J

Modeling Shipment Spot Pricing in the Australian Container Shipping Industry: Case of ASIA-OCEANIA trade lane.

Ubaid, A

Hussain, F

Charles, J

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Publisher:: Elsevier BV
Publication Type:: Journal Article
Citation:: Knowledge-based systems, 2020, 210, pp. 106483
Issue Date:: 2020-12

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Field	Value	Language
dc.contributor.author	Ubaid, A https://orcid.org/0000-0002-9833-9891
dc.contributor.author	Hussain, F https://orcid.org/0000-0003-1513-8072
dc.contributor.author	Charles, J
dc.date.accessioned	2021-03-07T05:51:31Z
dc.date.available	2020-09-24
dc.date.available	2021-03-07T05:51:31Z
dc.date.issued	2020-12
dc.identifier.citation	Knowledge-based systems, 2020, 210, pp. 106483
dc.identifier.issn	0950-7051
dc.identifier.issn	1872-7409
dc.identifier.uri	http://hdl.handle.net/10453/146848
dc.description.abstract	The shipping industry is fairly volatile pertaining to shipment pricing. To handle this volatility, two types of pricing strategies are employed in the shipping sector, contract market pricing and spot pricing. The contract market offers a fixed shipment price for a known cargo task over a set period, with secured booking space in periods of high demand. The spot market has a fluctuating shipment price, where one can benefit from lower prices than contract rate shipment prices in the low season, but face escalating shipment prices and less certainty of being able to secure a booking on a particular vessel in peak season, as space is reserved for contracted customers. However, both the pricing strategies followed have no relationship between current shipment demand and available shipping capacity and shipment prices are quoted based on predefined price lists (hard copy). This paper addresses the research gap of optimal spot shipment price calculation based on current shipment demand and available shipping capacity. To do so, we have developed a model that utilizes historical data to calculate spot pricing for container shipments. The proposed model is capable of calculating shipment spot prices based on shipment demand and capacity. Data from various sources was gathered to generate a shipping dataset for three years (i.e. from 2016 until 2018). Regression and correlation analysis are used to quantify research outcomes. Results have shown that the proposed model significantly increases the correlation between shipment price and shipment demand from 0.33 to 0.88 and available capacity from -0.12 to 0.35 respectively.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	Elsevier BV
dc.relation.ispartof	Knowledge-based systems
dc.relation.isbasedon	10.1016/j.knosys.2020.106483
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	08 Information and Computing Sciences, 15 Commerce, Management, Tourism and Services, 17 Psychology and Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Modeling Shipment Spot Pricing in the Australian Container Shipping Industry: Case of ASIA-OCEANIA trade lane.
dc.type	Journal Article
utslib.citation.volume	210
utslib.location.activity	Netherlands
utslib.for	0806 Information Systems
utslib.for	08 Information and Computing Sciences
utslib.for	15 Commerce, Management, Tourism and Services
utslib.for	17 Psychology and Cognitive Sciences
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
dc.date.updated	2021-03-07T05:51:16Z
pubs.publication-status	Published
pubs.volume	210

Abstract:

The shipping industry is fairly volatile pertaining to shipment pricing. To handle this volatility, two types of pricing strategies are employed in the shipping sector, contract market pricing and spot pricing. The contract market offers a fixed shipment price for a known cargo task over a set period, with secured booking space in periods of high demand. The spot market has a fluctuating shipment price, where one can benefit from lower prices than contract rate shipment prices in the low season, but face escalating shipment prices and less certainty of being able to secure a booking on a particular vessel in peak season, as space is reserved for contracted customers. However, both the pricing strategies followed have no relationship between current shipment demand and available shipping capacity and shipment prices are quoted based on predefined price lists (hard copy). This paper addresses the research gap of optimal spot shipment price calculation based on current shipment demand and available shipping capacity. To do so, we have developed a model that utilizes historical data to calculate spot pricing for container shipments. The proposed model is capable of calculating shipment spot prices based on shipment demand and capacity. Data from various sources was gathered to generate a shipping dataset for three years (i.e. from 2016 until 2018). Regression and correlation analysis are used to quantify research outcomes. Results have shown that the proposed model significantly increases the correlation between shipment price and shipment demand from 0.33 to 0.88 and available capacity from -0.12 to 0.35 respectively.

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http://hdl.handle.net/10453/146848