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arxiv: 2604.18767 · v2 · submitted 2026-04-20 · 💻 cs.CE · econ.GN· q-fin.EC

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Maritime Connectivity Vulnerability Index: Construction, Patterns, and Validation Across 185 Economies, 2006-2025

Mohamed Bouka , Moulaye Abdel Kader Moulaye Ismail
Authors on Pith no claims yet

Pith reviewed 2026-05-10 03:00 UTC · model grok-4.3

classification 💻 cs.CE econ.GNq-fin.EC
keywords maritime connectivityvulnerability indexliner shippingsupply chaintrade shockssmall island developing statesUNCTAD indicatorsCOVID-19 disruption
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The pith

A new Maritime Connectivity Vulnerability Index built from three UNCTAD indicators predicts which economies will lose the most trade during supply shocks.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper constructs the MCVI to measure structural vulnerability in liner shipping networks from the supply side, drawing on low overall connectivity, weak bilateral integration, and port infrastructure concentration. It applies the index to 185 economies from 2006 to 2025 and finds that small island developing states score higher on vulnerability, with port concentration as the dominant factor for nearly 40 percent of countries. Rankings remain stable under alternative methods, and the index correlates negatively with logistics performance and positively with freight rates. Pre-crisis MCVI scores forecast larger trade losses in the 2020 COVID supply shock but show the opposite pattern in the 2008-2009 demand shock, supporting the index's supply-side focus.

Core claim

The paper establishes that the MCVI, formed by equal-weight aggregation of fractional ranks from the LSCI, LSBCI, and PLSCI, captures supply-side maritime vulnerability. This produces a vulnerability paradox in which small, trade-dependent economies are both highly open and highly exposed. The index demonstrates external validity through negative correlation with the World Bank Logistics Performance Index and positive correlation with maritime freight rates, plus predictive power for trade losses specifically during supply shocks.

What carries the argument

The Maritime Connectivity Vulnerability Index (MCVI), formed by pooled fractional rank normalization followed by equal-weight aggregation of three UNCTAD indicators.

If this is right

  • Nearly 40 percent of economies face port concentration as their primary vulnerability driver, making infrastructure diversification a distinct policy priority.
  • Pre-crisis MCVI values can identify economies likely to suffer larger trade drops during future supply disruptions such as pandemics or chokepoint closures.
  • The gap in vulnerability between SIDS and non-SIDS economies widened slightly over two decades, indicating persistent structural exposure.
  • Panel regressions reveal a vulnerability paradox in which small, trade-dependent economies remain both the most open and the most exposed.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • MCVI scores could help prioritize maritime infrastructure investments or emergency aid toward the most exposed economies.
  • The index might be extended with real-time shipping data to provide ongoing risk monitoring beyond annual snapshots.
  • Its stability across weighting schemes suggests it can support consistent cross-country comparisons in policy reports.

Load-bearing premise

The three selected UNCTAD indicators fully capture structural maritime connectivity vulnerability from a supply-side perspective without major omissions.

What would settle it

A future supply shock in which pre-crisis MCVI scores show no negative correlation with observed trade volume losses would undermine the index's claimed predictive validity.

read the original abstract

Recent disruptions at major maritime chokepoints have exposed the structural fragility of liner shipping networks. Existing indicators measure connectivity, but none quantify its structural vulnerability from a supply-side perspective. We propose the Maritime Connectivity Vulnerability Index (MCVI), capturing three dimensions mapped to distinct UNCTAD sources: low overall connectivity (LSCI), weak bilateral integration (LSBCI), and port infrastructure concentration (PLSCI). The index covers 185 economies over 2006-2025 using pooled fractional rank normalization and equal-weight aggregation from publicly available data. SIDS exhibit a mean vulnerability 0.234 points above non-SIDS economies, with the gap widening from 0.232 to 0.249 over two decades. A modest global decline of 4.2% is observed. Port concentration dominates for nearly 40% of economies (72 of 185), establishing infrastructure diversification as a distinct policy priority. Rankings are highly stable across alternative weighting schemes, normalization methods (Spearman rho = 0.97-0.999), and PCA-derived weights; Monte Carlo simulation (1,000 replications) confirms rho > 0.95 in every realization. External validation shows strong negative correlation with the World Bank Logistics Performance Index (rho = -0.61 across seven waves) and positive correlation with ad valorem maritime freight rates (rho = +0.32). Panel regressions reveal a vulnerability paradox whereby small trade-dependent economies are simultaneously the most trade-open and the most vulnerable. Pre-crisis MCVI predicts trade losses during the COVID-19 supply shock (rho = -0.25, p < 0.005), while the contrasting positive correlation during the 2008-2009 demand shock (rho = +0.23, p = 0.01) validates the supply-side specificity of the index.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper constructs the Maritime Connectivity Vulnerability Index (MCVI) for 185 economies over 2006-2025 from three UNCTAD indicators (LSCI for overall connectivity, LSBCI for bilateral integration, and PLSCI for port concentration) using pooled fractional rank normalization and equal-weight aggregation. It reports patterns including higher vulnerability for SIDS (mean gap of 0.234, widening over time), dominance of port concentration for 72 economies, a 4.2% global decline, and extensive robustness (Monte Carlo rho > 0.95, Spearman 0.97-0.999 across alternatives). External validation includes rho = -0.61 with World Bank LPI and rho = +0.32 with freight rates; panel regressions show a vulnerability paradox for trade-dependent economies. The central claim is that pre-crisis MCVI predicts COVID-19 supply-shock trade losses (rho = -0.25, p < 0.005) while showing the opposite sign for the 2008 demand shock (rho = +0.23), validating supply-side specificity.

Significance. If the validation isolates a genuine supply-side maritime mechanism, the MCVI would provide a useful, replicable tool for identifying structurally vulnerable economies and prioritizing infrastructure diversification, especially for SIDS. Credit is due for the use of public UNCTAD data, the falsifiable contrast between supply and demand shocks, and the thorough robustness suite (Monte Carlo simulations, PCA weights, alternative normalizations) that supports stability of rankings.

major comments (2)
  1. [Abstract] Abstract and validation paragraph: The claim that the sign difference in correlations (rho = -0.25 for COVID supply shock vs. rho = +0.23 for 2008 demand shock) validates the supply-side specificity of the MCVI is load-bearing for the paper's central contribution. However, the index is built solely from LSCI, LSBCI, and PLSCI with no explicit chokepoint exposure term, despite the abstract motivating the work with chokepoint disruptions. Without regressions controlling for general trade openness or chokepoint proxies, the negative COVID correlation could reflect broader economic exposure rather than the claimed maritime supply-side channel.
  2. [Methods] Methods and construction section: The three indicators are asserted to comprehensively capture structural supply-side vulnerability, but PLSCI (port concentration) is only a partial proxy for chokepoint dependence. The paper should demonstrate that omitted factors such as route-level chokepoint exposure do not drive the reported correlations, for example by adding a supplementary specification that includes a chokepoint distance or exposure variable.
minor comments (2)
  1. [Data and methods] The abstract states the index covers 2006-2025 but does not clarify the latest available data year or whether 2024-2025 values involve imputation or projection; this should be stated explicitly in the data section.
  2. [Results] Table or figure presenting the SIDS vs. non-SIDS gap should include standard errors or confidence intervals to allow assessment of the reported widening from 0.232 to 0.249.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive and detailed comments on the validation approach and potential omitted factors in the MCVI. We respond to each major comment below, clarifying the scope of our index and validation while acknowledging limitations.

read point-by-point responses

  1. Referee: [Abstract] Abstract and validation paragraph: The claim that the sign difference in correlations (rho = -0.25 for COVID supply shock vs. rho = +0.23 for 2008 demand shock) validates the supply-side specificity of the MCVI is load-bearing for the paper's central contribution. However, the index is built solely from LSCI, LSBCI, and PLSCI with no explicit chokepoint exposure term, despite the abstract motivating the work with chokepoint disruptions. Without regressions controlling for general trade openness or chokepoint proxies, the negative COVID correlation could reflect broader economic exposure rather than the claimed maritime supply-side channel.

    Authors: We agree that the sign difference between the COVID-19 and 2008 correlations is central to demonstrating supply-side specificity. The MCVI is defined using the three UNCTAD indicators precisely to capture maritime connectivity dimensions relevant to supply disruptions, including through port concentration and overall connectivity. The opposite signs (negative correlation with trade losses in the supply shock versus positive in the demand shock) provide evidence against a purely general economic exposure interpretation, as broader openness would be expected to produce consistent directional associations. We will revise the abstract and validation section to more explicitly qualify the claim as suggestive rather than definitive and to note the absence of direct chokepoint controls as a limitation for future work. No new regressions with additional controls are feasible within the current UNCTAD-based dataset. revision: partial

  2. Referee: [Methods] Methods and construction section: The three indicators are asserted to comprehensively capture structural supply-side vulnerability, but PLSCI (port concentration) is only a partial proxy for chokepoint dependence. The paper should demonstrate that omitted factors such as route-level chokepoint exposure do not drive the reported correlations, for example by adding a supplementary specification that includes a chokepoint distance or exposure variable.

    Authors: We acknowledge that PLSCI functions as a proxy for port concentration and does not directly measure route-specific chokepoint exposure. The MCVI combines it with LSCI and LSBCI to reflect structural maritime vulnerability from a supply perspective. We will add clarifying language in the methods section on the proxy nature of PLSCI and discuss why route-level chokepoint data falls outside the UNCTAD sources used for the 185-economy panel. The existing robustness suite (Monte Carlo simulations with rho > 0.95, Spearman correlations of 0.97-0.999 across alternatives, and PCA weights) already addresses stability against alternative constructions. We do not add a new chokepoint specification in this revision. revision: partial

Circularity Check

0 steps flagged

No circularity: MCVI aggregates external UNCTAD indicators and validates against independent datasets

full rationale

The paper constructs MCVI via pooled fractional rank normalization and equal-weight aggregation of three pre-existing UNCTAD indicators (LSCI, LSBCI, PLSCI). No parameters are fitted to the validation targets (trade losses, LPI, freight rates). The reported correlations (e.g., rho = -0.25 with COVID trade losses) are computed after construction on separate external data and do not reduce to the index inputs by definition. Robustness checks (alternative weights, PCA, Monte Carlo) and cross-shock sign differences further demonstrate independence. No self-citations, self-definitional steps, or fitted-input predictions appear in the derivation chain.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 1 invented entities

The central claim rests on the assumption that the selected metrics capture vulnerability and on the choice of equal weighting and normalization method.

free parameters (1)
  • equal weights for the three dimensions
    The paper uses equal-weight aggregation without specifying optimization or justification from data.
axioms (1)
  • domain assumption The dimensions of low overall connectivity, weak bilateral integration, and port infrastructure concentration adequately represent structural vulnerability in liner shipping networks.
    Directly mapped from UNCTAD sources as the basis for the index.
invented entities (1)
  • Maritime Connectivity Vulnerability Index (MCVI) no independent evidence
    purpose: To quantify the structural fragility of maritime connectivity from a supply-side perspective.
    Newly defined composite index without independent empirical validation beyond the paper's correlations.

pith-pipeline@v0.9.0 · 5654 in / 1272 out tokens · 157834 ms · 2026-05-10T03:00:19.419796+00:00 · methodology

discussion (0)

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Reference graph

Works this paper leans on

50 extracted references · 14 canonical work pages

  1. [1]

    Analysis of the coupled spatial and temporal development characteristics of global liner shipping connectivity driven by trade.Ocean & Coastal Management, 251:107071, 2024

    Shu Guo, Jing Lu, and Yafeng Qin. Analysis of the coupled spatial and temporal development characteristics of global liner shipping connectivity driven by trade.Ocean & Coastal Management, 251:107071, 2024

    2024

  2. [2]

    Trade shocks and direct shipping connections: causal insights into network adaptability and supply chain resilience.WMU Journal of Maritime Affairs, pages 1–33, 2026

    Achilleas Tsantis, John Mangan, and Roberto Palacin. Trade shocks and direct shipping connections: causal insights into network adaptability and supply chain resilience.WMU Journal of Maritime Affairs, pages 1–33, 2026

    2026

  3. [3]

    Review of maritime transport 2024: Navigating maritime chokepoints

    United Nations Trade and Development (UNCTAD). Review of maritime transport 2024: Navigating maritime chokepoints. Technical report, United Nations, 2024

    2024

  4. [4]

    Mengqiao Xu, Yifan Zhu, Kaishuo Liu, and Adolf K. Y . Ng. Assessing resilience of global liner shipping network to tropical cyclones.Transportation Research Part D: Transport and Environment, 131:104189, 2024

    2024

  5. [5]

    Iran conflict and the Strait of Hormuz: Impacts on oil, gas, and other commodities, 2026

    Congressional Research Service. Iran conflict and the Strait of Hormuz: Impacts on oil, gas, and other commodities, 2026. CRS Report R45281

    2026

  6. [6]

    Advisory to shipping on draft restrictions, 2024

    Panama Canal Authority. Advisory to shipping on draft restrictions, 2024

    2024

  7. [7]

    Liner shipping connectivity.UNCTAD Transport Newsletter, 27:4–12, 2005

    Jan Hoffmann. Liner shipping connectivity.UNCTAD Transport Newsletter, 27:4–12, 2005. First Quarter 2005

    2005

  8. [8]

    Liner shipping connectivity index (LSCI): Methodology and data

    UNCTAD. Liner shipping connectivity index (LSCI): Methodology and data. UNCTADstat Data Centre, 2024. URLhttps://unctadstat.unctad.org/datacentre/dataviewer/US.LSCI

    2024

  9. [9]

    Building a dataset for bilateral maritime connectivity.UNCTAD Policy Issues in International Trade and Commodities, 2013

    Marco Fugazza, Jan Hoffmann, and Rado Razafinombana. Building a dataset for bilateral maritime connectivity.UNCTAD Policy Issues in International Trade and Commodities, 2013

    2013

  10. [10]

    The container port performance index 2020 to 2024: Trends and lessons learned

    World Bank and S&P Global Market Intelligence. The container port performance index 2020 to 2024: Trends and lessons learned. Technical report, World Bank Group, 2025

    2020

  11. [11]

    A metric of global maritime supply chain disruptions: The global supply chain stress index – maritime (GSCSI-M)

    Jean-François Arvis, Jean-Paul Rodrigue, Daria Ulybina, and Cordula Rastogi. A metric of global maritime supply chain disruptions: The global supply chain stress index – maritime (GSCSI-M). Journal of Transport Geography, 131:104575, 2026

    2026

  12. [12]

    Country-level vulnerability in maritime bulk commodity supply chains: An integrated framework for identification, monitoring, and extrapolation

    Lin Guo, Fangping Yu, Cong Sui, and Mo Yang. Country-level vulnerability in maritime bulk commodity supply chains: An integrated framework for identification, monitoring, and extrapolation. Systems, 14(2):120, 2026

    2026

  13. [13]

    Human development report 2023-24

    UNDP. Human development report 2023-24. Technical report, United Nations, 2024

    2023

  14. [14]

    Liner shipping connectivity as determinant of trade.Journal of Shipping and Trade, 2(1):1, 2017

    Marco Fugazza and Jan Hoffmann. Liner shipping connectivity as determinant of trade.Journal of Shipping and Trade, 2(1):1, 2017

    2017

  15. [15]

    Liner shipping bilateral connectivity and its impact on South Africa’s bilateral trade flows.Maritime Economics & Logistics, 22(3):473–499,

    Jan Hoffmann, Naima Saeed, and Sigbjørn Sødal. Liner shipping bilateral connectivity and its impact on South Africa’s bilateral trade flows.Maritime Economics & Logistics, 22(3):473–499,

  16. [16]

    doi: 10.1057/s41278-019-00124-8

    work page doi:10.1057/s41278-019-00124-8

  17. [17]

    New context calls for changing how we measure maritime 32 connectivity

    UNCTAD. New context calls for changing how we measure maritime 32 connectivity. UNCTAD News, 2024. URL https://unctad.org/news/ new-context-calls-changing-how-we-measure-maritime-connectivity

    2024

  18. [18]

    Marco Fugazza. Bilateral maritime connectivity since 2006: A primer using new Liner Shipping Bilateral Connectivity Index (LSBCI) calculations.UNCTAD Transport and Trade Facilitation Newsletter, 2019

    2006

  19. [19]

    Measuring foreland container port connectivity disaggregated by destination markets: An index for Short Sea Shipping services in Spanish ports

    Julián Martínez-Moya and María Feo-Valero. Measuring foreland container port connectivity disaggregated by destination markets: An index for Short Sea Shipping services in Spanish ports. Journal of Transport Geography, 89:102653, 2020

    2020

  20. [20]

    Julián Martínez-Moya, Amparo Mestre-Alcover, and Ramon Sala-Garrido. Connectivity and competitiveness of the major Mediterranean container ports using ‘Benefit-of-the-Doubt’ and ‘Common Sets of Weights’ methods in Data Envelopment Analysis.Maritime Economics & Logistics, 26(2):261–282, 2024

    2024

  21. [21]

    Bartholdi, Pisit Jarumaneeroj, and Amar Ramudhin

    John J. Bartholdi, Pisit Jarumaneeroj, and Amar Ramudhin. A new connectivity index for container ports.Maritime Economics & Logistics, 18(3):231–249, 2016

    2016

  22. [22]

    Port centrality and the Composite Connectivity Index: Introducing a new concept in assessing the attractiveness of hub ports.Maritime Economics & Logistics, 24(1):67–91, 2022

    Chuanxu Wang, Xiaohan Dou, and Hercules Haralambides. Port centrality and the Composite Connectivity Index: Introducing a new concept in assessing the attractiveness of hub ports.Maritime Economics & Logistics, 24(1):67–91, 2022

    2022

  23. [23]

    A robust ranking of maritime connectivity: revisiting UNCTAD’s liner shipping connectivity index (LSCI)

    Vikas Kumar Mishra, Bapi Dutta, Mark Goh, José Rui Figueira, and Salvatore Greco. A robust ranking of maritime connectivity: revisiting UNCTAD’s liner shipping connectivity index (LSCI). Maritime Economics & Logistics, 23(3):424–443, 2021

    2021

  24. [24]

    Exploring the vulnerability of transportation networks by entropy: A case study of Asia–Europe maritime transportation network

    Tao Wen, Qiuya Gao, Yu wang Chen, and Kang Hao Cheong. Exploring the vulnerability of transportation networks by entropy: A case study of Asia–Europe maritime transportation network. Reliability Engineering & System Safety, 226:108578, 2022. doi: 10.1016/j.ress.2022.108578

    work page doi:10.1016/j.ress.2022.108578 2022

  25. [25]

    Agustina Calatayud, John Mangan, and Roberto Palacin. Vulnerability of international freight flows to shipping network disruptions: A multiplex network perspective.Transportation Research Part E: Logistics and Transportation Review, 108:195–208, 2017

    2017

  26. [26]

    Assessing the efficiency and vulnerability of global liner shipping network.Global Networks, 2024

    Mengqiao Xu, Tao Li, Yifan Zhu, Wenhui Deng, and Yihui Shen. Assessing the efficiency and vulnerability of global liner shipping network.Global Networks, 2024. doi: 10.1111/glob.12445

    work page doi:10.1111/glob.12445 2024

  27. [27]

    Study on cascading failure vulnerability of the 21st-century Maritime Silk Road container shipping network.Journal of Transport Geography, 117:103891, 2024

    Liupeng Jiang, Guangsheng Wang, Xuejun Feng, Tong Yu, and Zhiyi Lei. Study on cascading failure vulnerability of the 21st-century Maritime Silk Road container shipping network.Journal of Transport Geography, 117:103891, 2024. doi: 10.1016/j.jtrangeo.2024.103891

    work page doi:10.1016/j.jtrangeo.2024.103891 2024

  28. [28]

    Koks, Sihan Li, and Jim W

    Jasper Verschuur, Elco E. Koks, Sihan Li, and Jim W. Hall. Multi-hazard risk to global port infrastructure and resulting trade and logistics losses.Communications Earth & Environment, 4:5, 2023

    2023

  29. [29]

    Koks, and Jim W

    Jasper Verschuur, Elco E. Koks, and Jim W. Hall. Ports’ criticality in international trade and global supply-chains.Nature Communications, 13:4351, 2022. doi: 10.1038/s41467-022-32070-0

    work page doi:10.1038/s41467-022-32070-0 2022

  30. [30]

    Port vulnerability assessment from a supply chain perspective.Ocean & Coastal Management, 213:105851, 2021

    Meizhi Jiang, Jing Lu, Zhuohua Qu, and Zaili Yang. Port vulnerability assessment from a supply chain perspective.Ocean & Coastal Management, 213:105851, 2021. doi: 10.1016/j.ocecoaman. 2021.105851. 33

    work page doi:10.1016/j.ocecoaman 2021

  31. [31]

    Disruptions and resilience in global container shipping and ports: the COVID-19 pandemic versus the 2008–2009 financial crisis

    Theo Notteboom, Thanos Pallis, and Jean-Paul Rodrigue. Disruptions and resilience in global container shipping and ports: the COVID-19 pandemic versus the 2008–2009 financial crisis. Maritime Economics & Logistics, 23(2):179–210, 2021

    2008

  32. [32]

    The Red Sea crisis: ramifications for vessel operations, shipping networks, and maritime supply chains.Maritime Economics & Logistics, 26(1):1–20, 2024

    Theo Notteboom, Hercules Haralambides, and Kevin Cullinane. The Red Sea crisis: ramifications for vessel operations, shipping networks, and maritime supply chains.Maritime Economics & Logistics, 26(1):1–20, 2024. doi: 10.1057/s41278-024-00287-z

    work page doi:10.1057/s41278-024-00287-z 2024

  33. [33]

    Shipping network disruption, vulnerability and resilience amidst geopolitical tensions.Maritime Business Review, 10(3):260–281,

    Wei Yim Yap, Zhongzhen Xiao, Zengyan Fan, and Huan Feng. Shipping network disruption, vulnerability and resilience amidst geopolitical tensions.Maritime Business Review, 10(3):260–281,

  34. [34]

    doi: 10.1108/MABR-01-2025-0007

    work page doi:10.1108/mabr-01-2025-0007 2025

  35. [35]

    The impacts of carbon pricing on maritime transport costs and their implications for developing economies

    Isabelle Rojon, Nicholas-Joseph Lazarou, Nishatabbas Rehmatulla, and Tristan Smith. The impacts of carbon pricing on maritime transport costs and their implications for developing economies. Marine Policy, 132:104653, 2021. doi: 10.1016/j.marpol.2021.104653

    work page doi:10.1016/j.marpol.2021.104653 2021

  36. [36]

    The impact of tropical storms on international trade: Evidence from Eastern Caribbean Small Island Developing States.Economics of Disasters and Climate Change, 7(2): 179–208, 2023

    Preeya Mohan. The impact of tropical storms on international trade: Evidence from Eastern Caribbean Small Island Developing States.Economics of Disasters and Climate Change, 7(2): 179–208, 2023. doi: 10.1007/s41885-023-00128-y

    work page doi:10.1007/s41885-023-00128-y 2023

  37. [37]

    Analysis of maritime connectivity in the Association of Southeast Asian Nations and small island developing States in the Pacific

    UNCTAD. Analysis of maritime connectivity in the Association of Southeast Asian Nations and small island developing States in the Pacific. Technical Report 18, Transport and Trade Facilitation Series, 2022

    2022

  38. [38]

    Shifting proximities

    David Guerrero, Patrick Nierat, Jean-Claude Thill, and Emmanuel Cohen. Shifting proximities. visualizing changes in the maritime connectivity of African countries (2006/2016).Maritime Policy & Management, 2022. doi: 10.1080/03088839.2022.2116657

    work page doi:10.1080/03088839.2022.2116657 2006

  39. [39]

    Regional integration and maritime connectivity across the maghreb seaport system.Journal of Transport Geography, 51:280–293, 2016

    Fatima Mohamed-Chérif and César Ducruet. Regional integration and maritime connectivity across the maghreb seaport system.Journal of Transport Geography, 51:280–293, 2016

    2016

  40. [40]

    Handbook on constructing composite indicators: Methodology and user guide

    OECD and JRC. Handbook on constructing composite indicators: Methodology and user guide. Technical report, OECD Publishing, 2008

    2008

  41. [41]

    On the methodological framework of composite indices: A review of the issues of weighting, aggregation, and robustness

    Salvatore Greco, Alessio Ishizaka, Menelaos Tasiou, and Gianpiero Torrisi. On the methodological framework of composite indices: A review of the issues of weighting, aggregation, and robustness. Social Indicators Research, 141(1):61–94, 2019

    2019

  42. [42]

    Szabó, Sándor Bozóki, Zsombor Szádoczki, and Áron Dénes Hartvig

    Adél Kelemen, Zsuzsa K. Szabó, Sándor Bozóki, Zsombor Szádoczki, and Áron Dénes Hartvig. A sensitivity analysis of composite indicators: Min/max thresholds.Environmental and Sustainability Indicators, 23:100453, 2024. doi: 10.1016/j.indic.2024.100453

    work page doi:10.1016/j.indic.2024.100453 2024

  43. [43]

    To weight or not to weight, that is the question: The design of a composite indicator of landscape fragmentation.Applied Sciences, 2021

    Andrea De Montis et al. To weight or not to weight, that is the question: The design of a composite indicator of landscape fragmentation.Applied Sciences, 2021

    2021

  44. [44]

    The Proteus composite index: Towards a better metric for global food security.World Development, 126:104709, 2020

    Oscar Maria Caccavale and Valerio Giuffrida. The Proteus composite index: Towards a better metric for global food security.World Development, 126:104709, 2020. doi: 10.1016/j.worlddev.2019. 104709

    work page doi:10.1016/j.worlddev.2019 2020

  45. [45]

    Capturing the impact of economic forces on the dry bulk freight market.Maritime Transport Research, 2:100018, 2021

    Vangelis Tsioumas, Yiannis Smirlis, and Stratos Papadimitriou. Capturing the impact of economic forces on the dry bulk freight market.Maritime Transport Research, 2:100018, 2021. doi: 10.1016/ j.martra.2021.100018. 34

    work page arXiv 2021

  46. [46]

    Uncertainty and sensitivity analysis techniques as tools for the quality assessment of composite indicators.Journal of the Royal Statistical Society: Series A, 168(2):307–323, 2005

    Michaela Saisana, Andrea Saltelli, and Stefano Tarantola. Uncertainty and sensitivity analysis techniques as tools for the quality assessment of composite indicators.Journal of the Royal Statistical Society: Series A, 168(2):307–323, 2005

    2005

  47. [47]

    John Wiley and Sons, 2008

    Andrea Saltelli, Marco Ratto, Terry Andres, Francesca Campolongo, Jessica Cariboni, Debora Gatelli, Michaela Saisana, and Stefano Tarantola.Global Sensitivity Analysis: The Primer. John Wiley and Sons, 2008

    2008

  48. [48]

    The container transport system during Covid-19: An analysis through the prism of complex networks.Transport Policy, 115:113–125, 2022

    David Guerrero, Lucie Letrouit, and Carlos Pais-Montes. The container transport system during Covid-19: An analysis through the prism of complex networks.Transport Policy, 115:113–125, 2022

    2022

  49. [49]

    Logistics performance index 2023

    World Bank. Logistics performance index 2023. Technical report, World Bank Group, 2023

    2023

  50. [50]

    Trade and transport cost dataset

    UNCTAD and World Bank. Trade and transport cost dataset. Technical report, United Nations, 2024

    2024