Big Data Optimization in Maritime Logistics

Brouer, Berit Dangaard; Karsten, Christian Vad; Pisinger, David

doi:10.1007/978-3-319-30265-2_14

Cited by 27 publications

(14 citation statements)

References 35 publications

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“…Big data and artificial intelligence (AI) are crucial components of data-driven decision-making in most industries (Liang and Liu 2018). The maritime industry is one of the oldest and traditional industries to still rely more on intuition than on data, due to the vast size of network and planning problems (Brouer, Karsten, and Pisinger 2016). Big data and AI have received considerable attention in recent years, through a number of publications, and some scholars have portrayed the concept of 'big data' as hype (d'Amore, Baggio, and Valdani 2015).…”

Section: Introductionmentioning

confidence: 99%

Big data and artificial intelligence in the maritime industry: a bibliometric review and future research directions

Munim

Dushenko

Jimenez

et al. 2020

Maritime Policy & Management

245

107

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This study provides a bibliometric review of 279 studies on the applications of big data and artificial intelligence (AI) in the maritime industry, published in 214 academic outlets, authored by 842 scholars. We extracted bibliographical data from the Web of Science database and analysed it using the Bibliometrix tool in R software. Based on citation analysis metrics, we revealed the most influential articles, journals, authors and institutions. Using the bibliographic coupling methodology, we identified four underlying research clusters: (1) digital transformation in maritime industry, (2) applications of big data from AIS, (3) energy efficiency and (4) predictive analytics. We analysed these clusters in detail and extracted future research questions. Besides, we present research collaboration networks on the institution and author level.

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Section: Introductionmentioning

confidence: 99%

Big data and artificial intelligence in the maritime industry: a bibliometric review and future research directions

Munim

Dushenko

Jimenez

et al. 2020

Maritime Policy & Management

245

107

View full text Add to dashboard Cite

show abstract

“…BDA have been used to gain competitive advantage and provide new services in logistics [61]. Maritime companies have also used prescriptive and predictive BDA to solve their planning problems [62]. In another study, we have used big data to share transportation capacity in order to improve the efficiency of urban healthcare services [63].…”

Section: Bda and Logisticsmentioning

confidence: 99%

Big Data Analytics and Its Applications in Supply Chain Management

Darvazeh¹,

Vanani²,

Musolu³

2020

New Trends in the Use of Artificial Intelligence for the Industry 4.0

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In today's competitive marketplace, development of information technology, rising customer expectations, economic globalization, and the other modern competitive priorities have forced organizations to change. Therefore, competition among enterprises is replaced by competition among enterprises and their supply chains. In current competitive environment, supply chain professionals are struggling in handling the huge data in order to reach integrated, efficient, effective, and agile supply chain. Hence, explosive growth in volume and different types of data throughout the supply chain has created the need to develop technologies that can intelligently and rapidly analyze large volume of data. Big data analytics capability (BDA) is one of the best techniques, which can help organizations to overcome their problem. BDA provides a tool for extracting valuable patterns and information in large volume of data. So, the main purpose of this book chapter is to explore the application of BDA in supply chain management (SCM).

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“…Brouer et al [5] go into more detail, showing how operational data can be used to build predictive models that can then provide input for the decision-making process. Optimization within maritime logistics is complicated due to the size of the network that carriers operate and the uncertainty caused by delays, fluctuations in demand, no-show cargo, etc.…”

Section: Logistics Optimization / Optimizacija Logistikementioning

confidence: 99%

“…Due to the size of the network that maritime logistics companies operate, they face large scale planning problems at the strategic, tactical and operational level [5]. Making decisions regarding maritime logistics to ensure safety, minimize cost and improve productivity means taking into account a large number of parameters susceptible to change.…”

Section: Introduction / Uvodmentioning

confidence: 99%

Veliki skupovi podataka u pomorskoj industriji

Mirović¹,

Miličević²,

Obradovic³

2018

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SummaryMaritime industry is a complex system that requires a quick adaptation to changing conditions and in which decision-making needs to take into account a large number of parameters. As navigation systems become more advanced, there is a significant amount of ship performance and navigation data generated. Big Data analytics tools make it possible to analyze these large quantities of data in order to gain the insight that supports decision-making. This paper gives an overview of the applications of Big Data in maritime industry, specifically in logistics optimization, safety and energy efficiency improvement, as well as the challenges that systems involving Big Data face. SažetakPomorska industrija je složeni sustav koji zahtijeva brzu prilagodbu u promjenjivim uvjetima u kojima je potrebno uzeti u obzir velik broj parametara prilikom donošenja odluka. Napretkom navigacijskih sustava, generira se znatna količina podataka o performansama broda i navigaciji. Analitički alati za velike skupove podataka omogućuju analizu tih podataka kako bi se dobilo razumijevanje potrebno za podršku donošenju odlukâ. Ovaj članak daje pregled primjene velikih skupova podataka u pomorstvu, posebno u optimizaciji logistike, sigurnosti i poboljšanju energetske učinkovitosti, kao i izazove s kojima se suočavaju sustavi koji koriste velike skupove podataka. KEY

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Big Data Optimization in Maritime Logistics

Cited by 27 publications

References 35 publications

Big data and artificial intelligence in the maritime industry: a bibliometric review and future research directions

Big data and artificial intelligence in the maritime industry: a bibliometric review and future research directions

Big Data Analytics and Its Applications in Supply Chain Management

Veliki skupovi podataka u pomorskoj industriji

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