An analysis of connectivity, assortativity and cluster structure of the Asian-Australasian cruise shipping network

Kanrak, Maneerat; Nguyen, Hong-Oanh

doi:10.1016/j.martra.2021.100048

Cited by 6 publications

(6 citation statements)

References 40 publications

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“…A complex network has been used to analyse maritime networks extensively, such as Ducruet and Zaidi (2012), Tsiotas et al . (2018), Kanrak and Nguyen (2022), Kanrak and Nguyen (2022) and Kanrak et al . (2022).…”

Section: Methodsmentioning

confidence: 96%

Cruise shipping network of ports in and around the emission control areas: a network structure perspective

Kanrak,

Lau,

Ling

et al. 2023

MABR

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PurposeThe rapid growth in cruise shipping coupled with increasing public awareness of climate change has led to increasing concerns about the impact cruise shipping poses on the environment, especially regarding air emissions. This study analyses the cruise shipping network of ports in and around the emission control areas (ECAs) to understand the structural properties of the network and ports.Design/methodology/approachA complex network approach was used to analyse the network data of 239 voyages serviced by 14 international cruise lines, visiting 127 ports across 44 countries in the Caribbean Sea.FindingsIt is found that the network has a small-world property with a short average path length and a high clustering coefficient. The regulations affect connections among ports, in which most ports in ECAs have lower connections than ports outside ECAs. A few ports in ECAs play important key roles, but many ports outside ECAs play a more important role in the network because the regulations are barriers for cruise ships entering the ports.Originality/valueThe findings of this study have drawn useful guidelines for cruise lines and port authorities to improve their operations. Constrictive recommendations are suggested to policymakers for designing reasonable regulations to attract more cruise shipping to travel in ECAs.

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Section: Methodsmentioning

confidence: 96%

Cruise shipping network of ports in and around the emission control areas: a network structure perspective

Kanrak,

Lau,

Ling

et al. 2023

MABR

Self Cite

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show abstract

“…This approach has been applied by many scholars to analyse many transport networks, such as Isaksen [45], Wang et al [46], Soh et al [47], Dai et al [48], Bombelli et al [49] and Hussain and Fusté-Forné [50]. Complex network analysis has also been used to analyse maritime transport networks, such as Hu and Zhu [51], Tsiotas and Polyzos [52], Ducruet [53], Tsiotas et al [37], Kanrak and Nguyen [13], Ducruet et al [54], Kanrak et al [35], Kanrak and Nguyen [33] and Gou and Wang [38]. In this study, analysis is conducted both at the network and port levels.…”

Section: Research Methods and Datamentioning

confidence: 99%

“…Cruise shipping network analysis explains the network of cruise ports (nodes) that are connected by cruise links (cruise routes). Different methods have been adopted to exhibit network connectivity, such as centrality measures, clustering coefficient, network density and average path length [33]. Kanrak and Nguyen [13,33,34] used assortativity, cluster structure, and connectivity of the cruise shipping network in the Asian-Australasian region.…”

Section: Studies On Cruise Shipping Networkmentioning

confidence: 99%

“…Different methods have been adopted to exhibit network connectivity, such as centrality measures, clustering coefficient, network density and average path length [33]. Kanrak and Nguyen [13,33,34] used assortativity, cluster structure, and connectivity of the cruise shipping network in the Asian-Australasian region. Kanrak et al [35] further analysed the change in the cruise shipping network by comparing the networks before and after the pandemic.…”

Section: Studies On Cruise Shipping Networkmentioning

confidence: 99%

“…This is completely suitable as an explanation of nodal accessibility that indicates the attractiveness of every specific node in a network considering the costs to access those nodes and the aggregation of other nodes via the network [39]. As such, a port has the greatest possible accessibility for cruise shipping implying the hub port in the network [33]. The cruise ship size can potentially be a limiting factor in accessing the port, and thus, the cruise traffic is concentrated on the specific market along with the network [40].…”

Section: Studies On Cruise Shipping Networkmentioning

confidence: 99%

See 2 more Smart Citations

Empirical Analysis of the Cruise Shipping Network in Asia

et al. 2023

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The cruise shipping market has been growing dynamically in the past two decades. This study presented an empirical analysis of the Asian cruise shipping network (ACSN) in which the nodes are cruise ports and links are cruise routes connecting the ports, using complex network analysis. An analysis of 245 voyages operated by 16 cruise lines between 215 ports in 26 countries found that ports in the ACSN are connected by 704 links. The ACSN is a small-world network with a small average path length and a high clustering coefficient, and its degree distribution follows an exponential function. A small number of ports have high connectivity, and most ports have low connections. Most high-degree ports connect to low-degree ports. The important roles and properties of ports vary depending on centrality measures.

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Modeling interactions in a dynamic heuristic business network

Kostelić,

Turk

2024

Appl Netw Sci

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This article presents a novel model for understanding the structure and dynamics of business networks, emphasizing the role of propensities to connect and cooperate as key drivers. The model incorporates behavioral elements and imperfect information updates, departing from traditional rational actor approaches. Starting from the theoretical background, several propositions are outlined, such as dynamism, connection choices, costs, strategy selection, information update, and the update based on experiences. Through simulations, the study successfully demonstrates that the proposed model effectively captures essential characteristics of business networks, including reciprocity, complexity, adaptation, and cooperation. The findings highlight the significance of propensities to connect and cooperate in shaping network structure, evolution, and stability. Particularly, higher propensities to cooperate and connect lead to denser and more cohesive networks, fostering reciprocity, stability, and network performance. The increase only in connection propensities does not have the same result. The lower cooperation propensities result in scale-free networks and asymmetrical distribution of cumulative payoffs. This highlights a crucial insight: different levels of cooperation lead to distinct network properties. Practical implications, increasingly relevant with the rise of digital platforms and metaverse, suggest targeted interventions to enhance network effectiveness, such as incentivizing cooperation, reducing relationship costs, and promoting a culture of trust and collaboration. While providing valuable insights, certain limitations exist, such as not considering the influence of preexisting economic or social structures, equalizing costs and payoffs among actors, and overlooking specific reasons for network connections. Future research should address these refinements and explore their effects on network structure and process characteristics.

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An analysis of connectivity, assortativity and cluster structure of the Asian-Australasian cruise shipping network

Cited by 6 publications

References 40 publications

Cruise shipping network of ports in and around the emission control areas: a network structure perspective

Cruise shipping network of ports in and around the emission control areas: a network structure perspective

Empirical Analysis of the Cruise Shipping Network in Asia

Modeling interactions in a dynamic heuristic business network

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