Data-Driven at Sea: Forecasting and Revenue Management at Molslinjen

被引：0

作者：

Pinson, Pierre ^{[1
,2
,3
]}

Bjorn, Mikkel ^{[1
]}

Kristiansen, Simon ^{[1
]}

Nielsen, Claus B. ^{[1
]}

Janerka, Lasse ^{[4
]}

Skovgaard, Jesper ^{[4
]}

Durhuus, Kristian ^{[4
]}

机构：

[1] Halfspace, DK-1306 Copenhagen, Denmark

[2] Imperial Coll London, Dyson Sch Design Engn, London SW7 2AZ, England

[3] Tech Univ Denmark, Dept Technol Management & Econ, DK-2800 Lyngby, Denmark

[4] Molslinjen, DK-8000 Aarhus, Denmark

来源：

INFORMS JOURNAL ON APPLIED ANALYTICS | 2025年 / 55卷 / 01期

关键词：

ferry operations; demand forecasting; revenue management; machine learning; Franz Edelman award; OPTIMIZATION;

D O I：

10.1287/inte.2024.0177

中图分类号：

C93 [管理学];

学科分类号：

12 ; 1201 ; 1202 ; 120202 ;

摘要：

Molslinjen, one of the world's largest operators of fast-moving catamaran ferries, based in Denmark, adopted a focus on digitalization to profoundly change its operations and business practices. Molslinjen partnered with Halfspace, a data, analytics, and artificial intelligence (AI) company based in Copenhagen, Denmark, to support that transition. Half- space and Molslinjen jointly developed and deployed a successful forecasting and revenue management toolbox for the data-driven operation of ferries in Denmark since 2020. This has resulted in $2.6-3.2 million yearly savings (and a total of $5 million savings as of December 2023), a significant reduction in the number of delayed departures and average delays, and a 3% reduction in fuel costs and emissions. This toolbox relies on some of the latest advances in machine learning for forecasting and in analytics approaches to revenue management. The potential for generalizing our toolbox to the global ferry industry is significant, with an impact on both revenues and environmental, societal, and governance criteria.

引用

页数：18

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