Evaluating alternative trade network configurations under geopolitical risk: a multi-scale systems approach

1 Introduction

Rising geopolitical tensions and supply-chain disruptions have generated growing academic and policy interest in more resilient and adaptive connectivity systems. For decades, international trade routes have relied heavily on maritime chokepoints such as the Strait of Hormuz, which serves as a vital route for global energy distribution. However, this heavy reliance on chokepoints also creates structural vulnerabilities to conflict, blockades, and non-traditional disruptions such as cyberattacks and environmental crises. Several reports from international organizations such as United Nations Conference on Trade and Development (2023) and the World Bank (2022) indicate that disruptions to these strategic routes could significantly impact energy price stability and the smooth flow of global trade. In this context, alternative distribution channels, including multimodal systems integrating maritime, land, and regional logistics routes, have received increasing attention as potential means of improving transport resilience.

In line with these concerns, several proposed trade corridors connecting the Middle East and Europe have received academic and policy attention, including configurations involving strategic hubs such as the Port of Tartous in Syria, the Kirkuk–Tripoli oil pipeline, and the Tapline connecting Saudi Arabia with Zahrani in Lebanon. These proposals provide possible alternatives for examining how reduced chokepoint dependency and greater route diversification could affect transport-system resilience. Theoretically, such configurations can be evaluated by integrating Geopolitical Risk Theory with a complex-systems approach, in which transport networks are understood as dynamic systems influenced by interacting structural, economic, and political conditions. The present study therefore compares alternative network configurations rather than assuming or empirically demonstrating an established transformation in global trade patterns.

Overall, from an analytical perspective, diversification from maritime chokepoints toward multimodal corridor configurations may alter the balance between efficiency, redundancy, and resilience in transport networks. Geopolitical risk represents one relevant condition affecting route planning, but it operates alongside commercial, infrastructural, technological, and operational considerations. Accordingly, this study does not treat geopolitical risk as the empirically established primary cause of global route reconfiguration. Instead, it evaluates how two alternative network configurations perform under specified geopolitical-risk and disruption assumptions.

The literature corpus in this review covers scientific publications published between 2019 and 2026. The geographic focus of the research is dominated by global maritime critical points such as the Straits of Hormuz, Malacca, and the Suez Canal, as well as land-sea transportation corridors in the Eurasian region (Sielker and Dannenberg, 2025; Wang et al., 2023). The research methodology shows a strong tendency towards quantitative approaches through the use of complex network modeling, geographic information system (GIS) simulations, and AIS-based spatiotemporal big data analysis (Alderson et al., 2020; Pratson, 2023). A small portion of the literature applies descriptive qualitative methods to dissect maritime security dynamics from an international relations perspective (Ramadhani and Marzaman, 2024; Rizkiyani et al., 2025).

These studies demonstrate convergence of findings regarding the Strait of Hormuz’s position as the most critical energy gateway determining the integrity of global supply chains (Meza et al., 2022; Sun et al., 2023). The closure or disruption of a single maritime chokepoint has been shown to trigger a domino effect, forcing systemic route reconfigurations and increasing global logistics operational costs (Pratson, 2023; Verschuur and Hall, 2024). However, there is divergence in assessing the economic impact of the Malacca Strait closure. Gao and Lu (2019) consider the impact of the Malacca Strait disruption to be relatively small for the fleet due to the existence of the Sunda Strait alternative. In contrast, Wang et al. (2023) classify it as a highly state-dependent route that is difficult to fully replace. This discrepancy stems from variations in measurement parameters between fleet cost optimization and actual vessel traffic density analyses.

The most dominant theoretical foundations in this literature are Multilayer Network Theory and complex network centrality analysis (Alderson et al., 2020; Sun et al., 2023). Researchers apply this framework to quantify the resilience of the global transportation system to physical disruptions and deliberate attacks. Realism theory in international relations is also used to explain the egoistic motivations of states in the Strait of Hormuz, which trigger anarchic actions in pursuit of national interests (Ramadhani and Marzaman, 2024). Furthermore, the concept of the “Economic Geography of War” provides a conceptual foundation for how military conflicts create new economic spaces that force permanent changes in trade routes (Sielker and Dannenberg, 2025). This theoretical foundation is highly relevant for analyzing the transition from maritime routes to land-based multimodal corridors.

The Strait of Hormuz recorded the highest geopolitical risk exposure index in the world, with a score of 264 due to persistent regional tensions (Soman and Balasubramanian, 2025). Disagreements in international law regarding transit rights between coastal and flag states have triggered a series of mine attacks and tanker detentions, hampering freedom of commercial navigation (Lott and Kawagishi, 2022). An escalation of military conflict in early 2026 resulted in a fivefold surge in war risk insurance premiums for shipping fleets compared to stable conditions (Ratner et al., 2026). Continued instability in this route has the potential to abruptly halt the distribution of 20% of global liquefied natural gas (LNG) supplies if key production facilities experience force majeure (Ratner et al., 2026). Adaptation strategies through route diversification and the development of supplementary trade corridors are a systemic necessity to maintain the continuity of the global energy supply chain (Soman and Balasubramanian, 2025).

A literature review identified significant thematic gaps regarding operational mechanisms and policy synchronization in a specific multimodal corridor connecting the Persian Gulf directly to the Mediterranean port of Tartous (Kalim and Syed, 2020; Sielker and Dannenberg, 2025) or to Tripoli or Zahrani in Lebanon. The current literature is limited to analyzing the economic impacts of maritime disruption without delving into the feasibility of integrating land routes across transit regions undergoing post-conflict recovery. The present study does not seek to resolve this route-level feasibility gap or to establish the corridor as an immediately operational substitute. Instead, it addresses a narrower analytical question by treating the Gulf–Levant–Europe corridor as a prospective network scenario through which the structural implications of route diversification can be examined. Infrastructure readiness, border-crossing efficiency, security conditions, legal and customs compatibility, political stability, insurance costs, and cargo-handling capability are therefore recognized as implementation constraints rather than empirically validated characteristics of the proposed corridor.

Existing research on global trade routes largely focuses on the vulnerability of maritime chokepoints, particularly the Strait of Hormuz, with comparatively limited assessment of how diversified multimodal configurations might perform under equivalent disruption conditions. Moreover, the literature remains fragmented across scales, with limited integration between macro-level geopolitical analysis, meso-level network structures, and micro-level operational performance. While quantitative models often overlook geopolitical dynamics, qualitative studies rarely incorporate technical or simulation-based analysis, resulting in a disconnect between risk assessment and transport system performance. In addition, current approaches are predominantly static and lack real-time, scenario-based tools to evaluate system adaptability under disruption conditions. Finally, emerging corridors linking the Middle East to Europe—especially through geopolitically sensitive or post-conflict regions—remain underexplored in terms of feasibility and resilience. This study addresses the systems-level and scenario-modeling dimensions of these gaps through an integrated multi-scale framework combining geopolitical risk analysis with dynamic, system-based modeling. Route-level operational and commercial feasibility, however, remains outside the scope of the present study.

2 The background

2.1 Strategic importance of the Strait of Hormuz in global energy trade

The Strait of Hormuz is one of the most strategically significant maritime passages in the world, given its central role in global energy transportation. Estimates indicate that approximately 20 million barrels of oil transit the strait daily, accounting for around 20–25% of total global seaborne oil trade (Schiffer, 2023). These figures reflect a high degree of flow concentration within a narrow geographic corridor, underscoring the strait’s exceptional geopolitical and economic importance.

Accordingly, the Strait of Hormuz is classified among the so-called “global chokepoints,” which are critical maritime passages that play a decisive role in the stability and security of international energy markets (Liu, 2023). Even localized disruptions in this corridor can generate far-reaching impacts, including sharp oil price volatility and significant disturbances in global supply chains.

2.2 Export structure through the strait of Hormuz

The Gulf littoral states constitute the primary exporters of oil transiting the strait, with exports highly concentrated among a limited number of countries, most notably Saudi Arabia, Iraq, United Arab Emirates, Kuwait, and Iran (Fattouh, 2021). These five countries collectively account for more than 90% of the total oil flows passing through the strait, with Saudi Arabia and Iraq leading in export volumes (Marzouk, 2025). However, the degree of dependence on the strait varies among these exporters. Some countries, particularly Saudi Arabia and the United Arab Emirates, possess partial alternatives through pipeline infrastructure that bypass the strait, whereas others, such as Iraq and Kuwait, remain almost entirely dependent on this route. This variation reflects differing levels of exposure to geopolitical risks associated with the chokepoint (EIA, 2017).

2.3 Import dependence and energy security implications

On the demand side, Asian economies represent the largest importers of oil transported through the strait, with major industrial economies such as China, India, Japan, and South Korea accounting for approximately 70–75% of total oil flows through the strait. This concentration highlights a high level of dependence on this critical maritime route (Schiffer, 2023). Such dependence underscores the strategic importance of the Strait of Hormuz for Asian energy security. Any disruption in oil flows through the strait could lead to immediate economic consequences, including rising energy costs, supply instability, and disruptions in industrial supply chains. Therefore, the stability of this passage is not merely a regional concern but a key determinant of global economic stability.

2.4 Constraints on navigation through the Strait of Hormuz

Navigation through the Strait of Hormuz is subject to a complex set of interrelated constraints that make it one of the most sensitive maritime passages globally. From a geopolitical perspective, the strait is located in a region characterized by persistent tensions, particularly between Iran and Western countries, increasing the likelihood of disruptions to maritime traffic due to military escalation or the strategic use of the strait as a pressure tool (Caldara and Iacoviello, 2022). From a security standpoint, risks include the targeting of commercial vessels through unconventional means, such as naval mines and unmanned aerial systems, which further complicate transport operations and necessitate enhanced protective measures. In addition, the strait’s geographical characteristics—namely its narrow navigational channels and high traffic density—impose operational constraints that elevate the risk of congestion and maritime accidents (Cordesman and Hwang, 2019). Collectively, these factors contribute to increased economic costs, including higher insurance premiums and operational expenses, which in turn directly affect global energy prices. Although partial alternatives exist, such as pipeline networks in Saudi Arabia and United Arab Emirates, their limited capacity is insufficient to offset any major disruption in oil flows through the strait. Consequently, the Strait of Hormuz remains a critical chokepoint that encapsulates the intersection of geopolitical, economic, and security dynamics in shaping global energy security (Wesley, 2007).

2.5 Multiroute commercial transit and network diversification

In contemporary global trade systems, the use of multiple routes represents a potential alternative to reliance on a single dominant pathway. Interest in this configuration reflects recognition that efficiency-driven, linear transport models—while cost-effective under stable conditions—are inherently vulnerable to disruption (Wesley, 2007). In contrast, multiroute configurations, which integrate maritime, land, and rail transport, enable the distribution of flows across parallel and complementary pathways, thereby reducing systemic exposure to localized risks.

From a network perspective, the use of multiple routes enhances structural redundancy and operational flexibility (Rodrigue, 2020). By dispersing trade flows across geographically distinct corridors, transport systems can mitigate the impact of disruptions affecting specific nodes or segments. This is particularly relevant in regions where strategic chokepoints, such as the Strait of Hormuz, concentrate a significant share of global energy and trade flows. In such contexts, alternative corridors—linking ports, inland logistics hubs, and cross-border rail networks—serve as critical buffers that enable partial rerouting and continuity of supply (Nagurney and Qiang, 2009).

Moreover, multiroute transit systems contribute to improved resilience by shortening exposure time and enhancing the adaptability of logistics operations. The availability of alternative pathways allows operators to dynamically adjust routing decisions in response to geopolitical developments, infrastructure constraints, or market fluctuations. This adaptability is increasingly supported by advances in logistics coordination, digital tracking systems, and integrated supply chain management (Sheffi, 2007). However, the transition toward multiroute transport does not eliminate risk; rather, it redistributes it across a broader spatial and operational framework. While diversification reduces dependence on single critical nodes, it may introduce new forms of complexity, including coordination challenges, regulatory fragmentation, and uneven infrastructure quality across routes. Nevertheless, from a systems-based perspective, the benefits of diversification—in terms of enhanced resilience, improved continuity, and reduced vulnerability to cascading disruptions—generally outweigh these challenges. Accordingly, multiroute commercial transit can be conceptualized as an alternative network configuration that places greater emphasis on resilience, flexibility, and risk management alongside cost efficiency in an increasingly uncertain geopolitical environment (Sheffi, 2007).

3 Research problem

The research problem of this study stems from the growing fragility of traditional trade transportation patterns that rely heavily on maritime chokepoints, which have long constituted the backbone of trade between the Middle East and Europe (Caldara and Iacoviello, 2022). The intensive dependence on a limited number of maritime passages—most notably the Strait of Hormuz—has led to a concentration of geopolitical risks within narrow geographic bottlenecks. This concentration renders trade and energy flows increasingly vulnerable to sudden disruptions that may escalate into large-scale systemic crises (Helbing, 2013). Amid rising regional tensions and increasing uncertainty in the global environment, the traditional model grounded solely in economic efficiency is no longer sufficient to explain or ensure the stability of transport systems (Buldyrev et al., 2010). Instead, there is a growing need to reconsider these systems through a systemic perspective that incorporates safety, resilience, and sustainability as emergent properties arising from network structures and their interactions (Lee and Rha, 2016).

In this context, proposed multimodal transport corridors linking the Middle East and Europe through integrated maritime, land, rail, and alternative logistics nodes provide an appropriate basis for scenario-based comparison with chokepoint-dependent systems. However, whether such configurations would improve systemic resilience or merely redistribute vulnerabilities across a wider geographical and political space remains an open analytical question. Accordingly, the research problem centers on comparing the performance of alternative network configurations under geopolitical-risk and disruption assumptions. Because the study does not track actual changes in cargo volumes and route utilization over an extended period, it does not claim that a broad global transition toward multimodal corridors is already underway. Rather, it is limited to evaluating this option within a set of hypothetical scenarios.

4 Theoretical framework

4.1 Integrated theoretical foundation

This study is grounded in an integrated theoretical framework that combines Geopolitical Risk Theory (Caldara and Iacoviello, 2022) with a systems-based approach (Helbing, 2013) to transport analysis. Geopolitical Risk Theory provides the basis for understanding how trade routes are shaped not only by economic efficiency but also by strategic considerations, including conflict exposure, political instability, and security concerns (Buldyrev et al., 2010). Within this perspective, critical maritime chokepoints, such as the Strait of Hormuz, are understood as points of both economic significance and systemic vulnerability. Complementing this, the study adopts a systems approach, in which transport networks are conceptualized as complex and interconnected systems rather than isolated routes (Helbing, 2013). In this framework, system performance is determined by the interaction between inputs (such as geopolitical risk and infrastructure capacity), network structure (including route diversification and connectivity), and outputs (namely safety, resilience, and sustainability). Safety, in particular, is interpreted as an emergent property reflecting the system’s ability to absorb and adapt to disruptions.

By integrating these two perspectives, the study evaluates chokepoint-dependent maritime transport and diversified multimodal corridors as alternative network configurations under geopolitical-risk conditions. The framework examines how geopolitical pressures may interact with network structure and influence system performance, without treating those pressures as the empirically established cause of an ongoing global reconfiguration.

4.2 Multi-scale analytical framework (macro–meso–micro)

This study adopts a multi-scale analytical framework to capture the complexity of transport system performance under conditions of geopolitical uncertainty. The framework distinguishes three interconnected levels of analysis: macro, meso, and micro. At the macro level, geopolitical risk represents the external environment within which transport systems operate, shaping overall exposure to disruption and uncertainty. At the meso level, the focus shifts to the structural characteristics of transport networks, including route diversification, rerouting capacity, and flow concentration, which determine the system’s ability to redistribute flows and maintain continuity under stress. At the micro level, system performance is operationalized through a quantitative evaluation model, namely the System Performance Index (SPI) and its weighted extension (WSPI), which integrates variables across both macro and meso levels. Through this hierarchical structure, the framework enables a comprehensive understanding of how external risks and internal network configurations interact to influence transport system resilience, thereby providing a coherent foundation for comparative analysis between chokepoint-dependent and multimodal transport systems.

Specifically, macro-level risk indicators are introduced into the WSPI model as weighting parameters, while meso-level network characteristics constitute the core performance variables, allowing the quantitative evaluation of how geopolitical pressures are translated into system resilience outcomes.

5 The relation between the theoretical framework and the research problem

To ensure analytical coherence across the three scales, this study establishes an explicit relational structure linking macro-level geopolitical risk, meso-level network configuration, and micro-level system performance. At the macro level, geopolitical risk is operationalized as an external stress variable that influences the probability and intensity of disruptions affecting transport systems. This risk is not treated as an isolated factor; rather, it propagates through the system by shaping meso-level network characteristics, particularly route diversification, flow concentration, and rerouting capacity. In turn, these meso-level structural properties determine how effectively the system can absorb and redistribute shocks. At the micro level, these interactions are quantified through the System Performance Index (SPI) and its weighted form (WSPI), where macro-level risk factors are incorporated as weighting coefficients, and meso-level indicators are translated into measurable variables. Accordingly, the SPI can be expressed as a function of both external risk exposure and internal network adaptability Equation 1:

SPI = f ( R macro , S meso ) (1)

where R macro represents geopolitical risk intensity and S mesodenotes structural network properties. The WSPI further operationalizes this relationship by assigning theory-informed weights that reflect the relative structural importance of the selected resilience and vulnerability indicators. Within this integrated framework, macro-level geopolitical exposure and meso-level network characteristics are incorporated into a scenario-based comparison of chokepoint-dependent and diversified multimodal transport configurations.

6 The results

6.1 The georisk and the transportation system

To facilitate a structured comparison between transport system configurations, a set of key performance indicators is presented in Table 1. The comparison in Table 1 demonstrates a clear structural contrast between the two systems. The chokepoint-based configuration shows extreme flow concentration, with approximately 20 million barrels per day passing through a single node, while only 13% of this volume can be rerouted in disruption scenarios. This results in a potential loss of up to 87% of flows, indicating a structurally fragile system. In contrast, the multimodal configuration distributes flows across multiple routes, reducing dependency on a single node and enabling partial rerouting. Although it does not match the volumetric capacity of the maritime system, it significantly improves system resilience by reducing exposure time and enabling adaptive responses.

Table 1. Comparison between the checkpoint and corridor system.

The analysis further shows that the available bypass capacity remains significantly limited. Alternative pipeline routes in Saudi Arabia and the UAE provide a combined capacity of approximately 2.6 million barrels per day, which accounts for only about 13% of the total volume transiting the chokepoint (U.S. Energy Information Administration (EIA), 2024). This disparity highlights a critical structural imbalance between flow concentration and redundancy, indicating that the system lacks sufficient buffering capacity to absorb disruptions without major consequences for global supply chains. In contrast, the emerging multimodal corridor configuration does not yet replicate the volumetric scale of maritime flows but introduces a different structural logic based on diversification and network flexibility. The integration of maritime, rail, and land transport through strategic nodes enables the redistribution of flows across multiple routes. Estimates suggest that the Gulf–Levant–Europe corridor could reduce transit time by up to 40% compared to traditional maritime routes via the Suez Canal (Kunaka and Carruthers, 2014). In addition, the operational capacity of the levant Port represents a functional component within emerging multimodal transport configurations. Available estimates indicate that the port handles several million tons of cargo annually, with container throughput ranging from tens of thousands to several hundred thousand TEU per year, depending on operational conditions and infrastructure development (Hasan, 2019). Although the reported cargo-handling capacity suggests that the port could function as a potential node within a multimodal network, these throughput figures alone do not establish its capacity to accommodate substantial Gulf–Europe cargo flows. Its effective integration would depend on infrastructure upgrades, reliable inland connections, border-processing capacity, security conditions, and operational coordination across the participating jurisdictions. From a systems perspective, the inclusion of such nodes enhances network connectivity and supports the redistribution of trade flows across multiple routes, thereby reducing dependence on single critical pathways and improving overall system flexibility (Rodrigue, 2020; Kunaka and Carruthers, 2014).

The comparison indicates that while the maritime chokepoint system maximizes efficiency under stable conditions, it remains highly sensitive to disruption due to its centralized structure. By contrast, the multimodal system enhances resilience by reducing dependence on single critical nodes and enabling rerouting capabilities. However, the comparison also indicates that diversification does not eliminate risk; under the evaluated scenario, it redistributes exposure across a wider geographical and political space. Consequently, the potential improvement in systemic resilience arises from the assumed network redundancy and rerouting capability rather than from the removal of geopolitical risk. These results describe the relative performance of the two configurations under the model assumptions and should not be interpreted as evidence that global transport systems are already undergoing an established transition from efficiency-driven to resilience-oriented design.

6.2 Comparative system performance analysis

6.2.1 Quantitative operationalization of the WSPI model

To provide a structured numerical comparison, the proposed System Resilience Performance Index (SPI) is operationalized as a resilience-oriented multi-criteria measure. The index compares selected structural characteristics of the chokepoint-based maritime configuration and the diversified multimodal corridor scenario. It does not represent a comprehensive assessment of their economic, environmental, or operational performance. The unweighted SPI is expressed as Equation 2:

SPI = D + R + A C + T + G (2)

where D denotes route diversification, R denotes rerouting capacity, and A denotes alternative capacity, whereas C, T, and G represent flow concentration, transit time, and geopolitical exposure, respectively. To account for the assumed differences in the relative structural importance of the selected indicators, the SPI is extended into the following weighted form Equation 3:

WSPI = w 1 D + w 2 R + w 3 A w 4 C + w 5 T + w 6 G (3)

where w i denotes the theory-informed weight assigned to each indicator. These weights are used as analytical coefficients to operationalize the scenario-based comparison and were not derived through a formal expert-elicitation or pairwise-comparison procedure. In this study, the resilience-side weights were assigned as follows:

w 1 = 0.40 for route diversification,

w 2 = 0.35 for rerouting capacity, and

w 3 = 0.25 for alternative capacity.

The vulnerability-side weights were assigned as:

w 4 = 0.45 for flow concentration,

w 5 = 0.30 for transit time, and

w 6 = 0.25 for geopolitical exposure.

Accordingly, the WSPI should be interpreted as a limited resilience-related performance construct rather than a comprehensive measure of overall transport-system superiority. It evaluates only the selected dimensions of route diversification, rerouting capacity, alternative capacity, flow concentration, transit time, and geopolitical exposure. It does not incorporate transport costs, energy efficiency, emissions, cargo-handling and transshipment requirements, border-crossing delays, infrastructure investment, financing requirements, or broader economic feasibility. A higher WSPI therefore indicates a more favorable resilience-oriented network structure under the adopted assumptions, but it does not demonstrate that the corresponding corridor is commercially attractive, environmentally preferable, operationally feasible, or economically superior.

6.2.2 Indicator normalization and scoring criteria

To make the conversion of system characteristics into ordinal scores transparent, each indicator was evaluated using the predefined operational criteria presented in Table 2. Indicators supported by comparable quantitative information were classified according to explicit numerical ranges. Indicators for which continuous and directly comparable data were unavailable were evaluated using defined operational categories. The resulting five-point scores should therefore be interpreted as scenario-based analytical classifications rather than direct empirical measurements. Table 3 identifies the observed evidence or scenario assumption underlying each baseline score. Because some classifications remain dependent on analytical judgment, their influence on the WSPI results was subsequently examined through equal-weight recalculation and bounded score-uncertainty analysis.

Table 2. Operational criteria for assigning scores on the five-point ordinal scale.

The thresholds are predefined operational classifications developed for the present scenario-based comparison and should not be interpreted as universally established transport-sector standards. Route diversification refers to the number of independent route options available within the evaluated configuration. Rerouting capacity refers to the proportion of disrupted flow that can be operationally redirected through connected alternative routes within the disruption scenario. Alternative capacity refers to the proportion of normal system flow that can be physically accommodated by the available bypass infrastructure. Flow concentration refers to the proportion of total system flow passing through the largest critical node. Transit time is measured in days.

Table 3. Baseline ordinal scores and their evidentiary or scenario basis.

Geopolitical exposure was assessed across five predefined dimensions: armed-conflict exposure, interstate tensions, border-related uncertainty, sanctions or regulatory restrictions, and threats to transport infrastructure. The geopolitical-exposure score was assigned according to the number of dimensions materially affecting each configuration. Where directly observed values were unavailable for the prospective multimodal corridor, the corresponding classifications were explicitly treated as scenario assumptions rather than empirical measurements.

Rerouting capacity and alternative capacity were treated as conceptually distinct indicators. Rerouting capacity measures the proportion of disrupted flow that can be redirected operationally within the evaluated disruption scenario, whereas alternative capacity measures the physical throughput available in the bypass infrastructure relative to normal system flow. Consequently, the documented 13% bypass capacity of the Hormuz-centered system was used to determine its alternative-capacity score and was not automatically treated as its operational rerouting rate.

6.2.3 Baseline input scores for the two configurations

Table 3 presents the baseline ordinal scores used in the WSPI calculation and identifies whether the basis of each score is an observed characteristic supported by the available evidence or an explicit scenario assumption. The Hormuz-centered configuration is assessed mainly using the documented characteristics discussed in the preceding sections. Because the proposed multimodal corridor is not yet a fully integrated and operational system, its scores represent analytical assumptions describing the network configuration evaluated in the scenario. These assumptions are subsequently varied in the bounded uncertainty analysis.

The baseline scores illustrate the structural differences assumed between the two configurations. However, they should not be interpreted as direct measurements of the overall performance or feasibility of either system. In particular, the multimodal-corridor values describe a prospective scenario rather than the observed performance of a fully operational corridor. Their influence on the resulting WSPI values is therefore examined through alternative weighting and bounded score variations. The Gulf–Levant–Europe configuration evaluated in this study should therefore be understood as a prospective scenario rather than an established or fully operational corridor. The analysis does not independently verify the present adequacy of route-specific infrastructure capacity, border-crossing arrangements, security conditions, legal and customs frameworks, political stability, insurance availability and cost, or cargo-handling capability. These factors are particularly uncertain because parts of the proposed network extend through geopolitically sensitive and post-conflict areas. The assigned corridor scores describe the structural configuration evaluated under the stated assumptions and should not be interpreted as evidence of current operational readiness.

6.2.4 Explicit WSPI calculation

The weights presented in Section 6.2.1 were theoretically assigned according to the relative structural importance of the selected indicators within the resilience-oriented framework. On the resilience side, route diversification (D) was assigned the highest weight (w D = 0.40) because it represents the primary structural condition for reducing dependence on a single pathway and introducing network redundancy. Rerouting capacity (R) was assigned a weight of w R = 0.35, reflecting its role in enabling flows to be redirected when the principal route is disrupted. Alternative capacity (A) was assigned a comparatively lower weight of w A = 0.25, as it represents the additional capacity available to accommodate diverted flows.

On the vulnerability side, flow concentration (C) was assigned the highest weight (w C = 0.45) because dependence on a single critical node constitutes a major structural source of disruption exposure. Transit time (T) was assigned a weight of w T = 0.30, reflecting its influence on the duration of exposure and operational continuity. Geopolitical exposure (G) was assigned a weight of w G = 0.25to represent the external political and security conditions that may affect transport-network continuity.

These weights were not empirically estimated or derived through expert elicitation, pairwise comparisons, or a formal multi-criteria weighting procedure. They should therefore be interpreted as theory-informed analytical assumptions used to operationalize the scenario-based comparison. To evaluate the extent to which the results depend on these assumptions, the baseline findings are subsequently compared with an equal-weight specification and bounded variations in the indicator scores Equations 4–9.

(a) Maritime chokepoint system.

For the Strait of Hormuz-centered system:

WSP I maritime = ( 0.40 × 1 ) + ( 0.35 × 1 ) + ( 0.25 × 2 ) ( 0.45 × 5 ) + ( 0.30 × 4 ) + ( 0.25 × 5 ) (4)

WSP I maritime = 0.40 + 0.35 + 0.50 2.25 + 1.20 + 1.25 (5)

WSP I maritime = 1.25 4.70 = 0.27 (6)

(b) Multimodal corridor system

For the Gulf–Levant–Europe multimodal corridor:

WSP I multimodal = ( 0.40 × 4 ) + ( 0.35 × 4 ) + ( 0.25 × 3 ) ( 0.45 × 2 ) + ( 0.30 × 2 ) + ( 0.25 × 3 ) (7)

WSP I multimodal = 1.60 + 1.40 + 0.75 0.90 + 0.60 + 0.75 (8)

WSP I multimodal = 3.75 2.25 = 1.67 (9)

6.2.5 Comparative results

The calculated results show a substantial difference in resilience-oriented performance between the two evaluated configurations under the adopted assumptions. The maritime chokepoint configuration records a WSPI value of 0.27, indicating limited structural adaptability and high vulnerability within the dimensions included in the index. In contrast, the prospective multimodal configuration achieves a WSPI value of 1.67, reflecting a more favorable balance between the selected resilience and vulnerability indicators. This difference indicates that network diversification and risk distribution influence the resilience-related construct measured by the WSPI. It should not be interpreted as evidence of the multimodal corridor’s overall transport-system superiority, commercial attractiveness, environmental performance, or operational and economic feasibility (see Table 4).

Table 4. WSPI comparison between the two systems.

6.2.6 Interpretation of the numerical results

The WSPI results confirm that the chokepoint-based maritime system remains highly efficient under stable conditions but performs poorly when evaluated through a resilience-oriented framework. Its very low score is driven mainly by three factors: extreme flow concentration, long transit exposure, and elevated geopolitical risk. By contrast, the multimodal system benefits from higher diversification and rerouting capacity, which compensate for its lower absolute throughput and produce a considerably higher system performance score. Accordingly, the numerical comparison indicates that, under the adopted assumptions, the diversified corridor configuration achieves a higher resilience-oriented performance score by distributing flows across multiple routes. This result represents a comparison between modeled configurations and does not demonstrate an observed transition in actual global trade routes.

Accordingly, the higher WSPI obtained by the multimodal-corridor scenario indicates potential resilience advantages associated with diversification under the adopted assumptions. It does not demonstrate that the corridor is presently operationally feasible, commercially viable, or capable of accommodating cargo volumes comparable to those passing through the Strait of Hormuz. Establishing such feasibility would require a separate route-level assessment incorporating infrastructure condition and throughput, border-crossing times, customs and legal compatibility, security exposure, political stability, insurance premiums, cargo-handling performance, and required capital investment.

6.2.7 Sensitivity and uncertainty analysis

The robustness of the WSPI comparison was examined through four complementary specifications: equal indicator weights, a conservative alternative-scoring scenario, a hybrid continuous-ordinal specification, and bounded ordinal-score uncertainty.

6.2.7.1 Equal-weight specification

Under the first robustness specification, the WSPI calculations were repeated using equal weights of 1/3 for each indicator within the resilience and vulnerability components. Under this specification, the WSPI of the Hormuz-centered configuration increased slightly from the baseline value of 0.27 to 0.29, whereas that of the multimodal-corridor scenario decreased from 1.67 to 1.57. The relative ranking therefore remained unchanged under the equal-weight specification.

6.2.7.2 Conservative alternative-scoring scenario

In addition to the equal-weight specification, an alternative scoring rule was applied to examine whether the baseline comparison was dependent on the relatively favorable classifications assigned to the prospective multimodal corridor. Under this conservative specification, each resilience score of the multimodal configuration was reduced by one point, while each vulnerability score was increased by one point, subject to the limits of the 1–5 scale. Accordingly, route diversification, rerouting capacity, and alternative capacity were reassigned scores of 3, 3, and 2, respectively, while flow concentration, transit time, and geopolitical exposure were reassigned scores of 3, 3, and 4 (see Table 5).

R multi , conservative = ( 0.40 × 3 ) + ( 0.35 × 3 ) + ( 0.25 × 2 ) = 2.75 (10)

V multi , conservative = ( 0.45 × 3 ) + ( 0.30 × 3 ) + ( 0.25 × 4 ) = 3.25 (11)

WSPI multi , conservative = 2.75 / 3.25 = 0.85 (12)

Table 5. Conservative alternative-scoring scenario for the multimodal corridor.

Under this conservative alternative-scoring rule, the multimodal-corridor WSPI decreased from 1.67 to 0.85. Although its estimated advantage was substantially reduced, it remained above the baseline Hormuz-centered value of 0.27. This result indicates that the comparative conclusion does not depend exclusively on the baseline scoring of the prospective corridor. Nevertheless, the reduced magnitude of the difference demonstrates that the results remain sensitive to the assumptions used to represent the multimodal configuration.

6.2.7.3 Hybrid continuous-ordinal robustness analysis

A fully continuous specification could not be implemented consistently across all six indicators because directly comparable quantitative data were unavailable for several characteristics of the prospective multimodal corridor. Therefore, a supplementary hybrid continuous-ordinal specification was employed using continuous values where comparable numerical inputs were available, while retaining ordinal classifications for rerouting capacity and geopolitical exposure. This approach provides a partial continuous robustness assessment without presenting scenario assumptions as fully observed measurements.

The underlying quantitative values were retained for route diversification, alternative capacity, flow concentration, and transit time. Route diversification was expressed relative to a five-route reference maximum. Alternative capacity and flow concentration were expressed as proportions of total system flow. Transit time was normalized against the predefined analytical range of 8–24 days. To maintain comparability with the 1–5 WSPI scale, the continuous values were linearly rescaled, while values falling outside the reference range were bounded at the scale limits. The central values of the scenario ranges were used for the prospective multimodal-corridor assumptions (see Table 6).

D ∗ = 1 + 4 [ ( n − 1 ) / 4 ] (13)

A ∗ = 1 + 4A (14)

C ∗ = 1 + 4C (15)

T ∗ = 1 + 4 [ ( T − 8 ) / 16 ] (16)

WSPIHormuz , hybrid = [ ( 0.40 × 1 ) + ( 0.35 × 1 ) + ( 0.25 × 1.52 ) ] / [ ( 0.45 × 4.20 ) + ( 0.30 × 4 ) + ( 0.25 × 5 ) ] ≈ 0.26 (17)

WSPImulti , hybrid = [ ( 0.40 × 4 ) + ( 0.35 × 4 ) + ( 0.25 × 2.50 ) ] / [ ( 0.45 × 2.20 ) + ( 0.30 × 2 ) + ( 0.25 × 3 ) ] ≈ 1.55 (18)

Table 6. Inputs used in the hybrid continuous-ordinal robustness analysis.

The hybrid specification produced WSPI values of approximately 0.26 for the Hormuz-centered configuration and 1.55 for the multimodal-corridor scenario, compared with baseline ordinal values of 0.27 and 1.67, respectively. The relative ranking therefore remained unchanged. However, because several multimodal inputs are scenario midpoints rather than direct observations, this analysis is interpreted as a robustness assessment rather than as evidence of observed corridor performance.

6.2.7.4 Bounded ordinal-score uncertainty

Finally, uncertainty in the ordinal classifications was examined by allowing each baseline indicator score to vary by ±1 point within the limits of the 1–5 scale. The lower WSPI bound was calculated by simultaneously decreasing the resilience scores and increasing the vulnerability scores. The upper bound was calculated by increasing the resilience scores and decreasing the vulnerability scores. This procedure produced bounded WSPI ranges of 0.20–0.61 for the Hormuz-centered configuration and 0.85–3.80 for the multimodal-corridor scenario. Although the magnitude of the difference varied substantially, the ranges did not overlap, and the multimodal configuration retained the higher resilience-oriented WSPI under the tested score perturbations.

These ranges represent bounded scenario uncertainty rather than statistical confidence intervals. The analysis indicates that the comparative ranking is robust to the examined weighting and scoring variations, although the precise WSPI values remain dependent on the selected indicators, operational thresholds, and theory-informed weights.

Across the equal-weight, conservative alternative-scoring, hybrid continuous-ordinal, and bounded uncertainty specifications, the multimodal configuration retained the higher WSPI. However, the magnitude of the difference varied considerably across specifications. The findings therefore support the robustness of the comparative ranking within the evaluated scenarios, but they do not establish the observed superiority or full operational feasibility of the prospective multimodal corridor.

6.2.8 Development of the python-based computational tool

To support the transparent and reproducible calculation of the Weighted System Performance Index (WSPI), a dedicated Python program was developed to implement the proposed analytical framework. The program processes the normalized indicator scores, applies the theory-informed weights, calculates the weighted resilience and vulnerability components, and generates the resulting WSPI values for each transport-network configuration (see Figure 1).

The program also generates numerical and visual outputs, including normalized indicator distributions, weighted indicator contributions, resilience and vulnerability components, and comparative WSPI values. In addition, the sensitivity-analysis module recalculates the WSPI under equal indicator weights, implements the conservative alternative-scoring scenario, applies the hybrid continuous–ordinal specification, and evaluates bounded score uncertainty by varying the baseline ordinal scores by ±1 within the permitted range of 1–5.

The Python-based implementation improves computational transparency and reduces the possibility of manual calculation errors. Its reproducibility refers specifically to the execution of the stated calculations using the supplied weights and indicator scores; it does not independently validate the theoretical assumptions underlying those inputs. Figure 2 presents the computational workflow, beginning with the input of the normalized ordinal scores, followed by the application of theory-informed weights, calculation of the resilience and vulnerability components, generation of the WSPI values, and implementation of the sensitivity analysis.

Following the execution of the developed Python program, the resulting outputs provide a quantitative evaluation of the two transport system configurations under study. The computed values include the weighted resilience components, vulnerability components, and the final Weighted System Performance Index (WSPI) for each system. In addition, the program generates a set of visual representations, including comparative indicator distributions, weighted component analysis, overall WSPI comparison, and sensitivity assessment. These results provide a structured exploratory basis for the scenario-based comparison of the two transport-network configurations, enabling a clear and systematic interpretation of differences in resilience-oriented performance and geopolitical-risk exposure between the maritime chokepoint system and the multimodal corridor system. Figure 3 shows the Normalized indicator comparison. Figure 4) shows the weighted WSPI. Figure 5A shows the Final WSPI comparison. Figure 5B summarizes the baseline WSPI values, the point estimates obtained under the three alternative specifications, and the bounded ordinal-score uncertainty ranges.

7 Interpretation of results in light of the theoretical framework

The findings are interpreted through an integrated framework combining Geopolitical Risk Theory with a systems-based approach. Within the evaluated scenarios, the results illustrate how geopolitical exposure and network structure may jointly influence transport-system performance. They do not, however, establish that geopolitical risk is the primary causal driver of an ongoing reconfiguration of actual trade routes. From the perspective of Geopolitical Risk Theory, the high concentration of flows through the Strait of Hormuz represents a typical case of “risk concentration,” where economic significance intersects with security vulnerability. The passage of approximately 20 million barrels per day through a single geographic point illustrates how a localized geopolitical factor can escalate into a global systemic threat, consistent with the theory’s assumption that trade routes are shaped by the interaction of economic, political, and security dynamics. From a systems perspective, these results reveal a clear structural imbalance between efficiency and resilience within the transport system. The high volume of flows, coupled with the limited bypass capacity of only 2.6 million barrels per day, indicates a deficiency in redundancy, which is a fundamental component of safety in complex systems. According to this framework, a system lacking sufficient alternative routes is highly susceptible to cascading failures when exposed to disruptions, thereby explaining the sensitivity of chokepoint-dependent maritime systems despite their high efficiency under stable conditions.

In contrast, the characteristics of the multimodal system can be interpreted within the same framework but lead to different implications. From a geopolitical risk perspective, the introduction of alternative corridors through nodes such as the Port of Levant reflects an effort to reduce direct exposure to geopolitical tension points rather than merely a logistical improvement (Caldara and Iacoviello, 2022). From a systems perspective, increased route diversification and enhanced network connectivity strengthen the system’s adaptive capacity. The potential reduction in transit time by up to 40%, along with improved rerouting capabilities, contributes to minimizing disruption duration and mitigating the impact of shocks (Black, 2015).

The findings also confirm a central assumption of the theoretical framework, namely that safety in transport systems is not achieved through the elimination of risk but through its management. The multimodal system does not eliminate geopolitical threats; instead, it redistributes them across a broader geographical space, thereby reducing the likelihood of total system failure. In this sense, safety emerges as a property of network structure rather than a function of any single transport mode.

In light of these observations, the results support the theoretical proposition that resilience-oriented network configurations may offer advantages under disruption conditions. The comparison illustrates the potential value of redundancy and rerouting capacity when geopolitical exposure is incorporated into transport-system evaluation. However, because the study does not analyze longitudinal route, investment, or cargo-flow data, it cannot determine whether transport-system design is undergoing a broad historical transition or whether geopolitical risk is the primary cause of any observed reconfiguration.

8 Conclusion

This study provides a scenario-based comparison between a chokepoint-dependent maritime system centered on the Strait of Hormuz and a prospective diversified multimodal corridor linking the Gulf, the Levant, and Europe. By integrating Geopolitical Risk Theory with a systems-based approach, the study evaluates how geopolitical exposure and network structure may interact to influence transport-system performance under disruption conditions. The analysis compares two alternative network configurations and does not seek to demonstrate that a global transition toward multimodal corridors is currently occurring or that geopolitical risk is its primary causal driver.

The differences between the evaluated configurations can be interpreted through the multi-scale analytical framework adopted in this study. At the macro level, geopolitical risk is treated as an external condition that may increase disruption exposure and influence the attractiveness of alternative route configurations. At the meso level, network structure determines how effectively flows can be redistributed when a critical node is disrupted. The chokepoint-based configuration is characterized by high flow concentration, limited alternative capacity, and weak rerouting capability, whereas the prospective multimodal configuration assumes greater route diversification, distributed connectivity, and enhanced rerouting potential. At the micro level, these structural differences are operationalized through the Weighted System Performance Index (WSPI).

Under the baseline assumptions, the maritime chokepoint configuration recorded a WSPI value of 0.27, compared with 1.67 for the prospective multimodal configuration. This difference indicates that, within the evaluated scenario, a more diversified network may achieve higher resilience-oriented performance through greater redundancy and rerouting flexibility. The result does not indicate the observed superiority of an existing corridor or establish that a reconfiguration of actual global trade routes has already taken place. Rather, it demonstrates how different network structures perform when assessed under a common set of geopolitical-risk and disruption assumptions.

The sensitivity and robustness analyses provide additional qualification of this comparison. The multimodal configuration retained the higher WSPI under the equal-weight, conservative alternative-scoring, hybrid continuous–ordinal, and bounded uncertainty specifications. However, the magnitude of its estimated advantage varied considerably across the tested specifications. The comparative ranking is therefore robust within the evaluated scenarios, while the size of the difference remains sensitive to the assumptions used to represent the prospective corridor. This sensitivity is particularly important because several inputs relating to the multimodal configuration represent analytical assumptions rather than directly observed operational measurements.

The findings further indicate that diversification does not eliminate geopolitical or operational risk. Instead, it may redistribute exposure across a broader spatial, institutional, and political environment. Greater route diversity can reduce dependence on a single critical node, but it may also introduce coordination challenges, regulatory fragmentation, border delays, security exposure, and uneven infrastructure quality. Accordingly, the higher WSPI of the multimodal configuration should be interpreted as a potential structural resilience advantage under the adopted assumptions, rather than as evidence of its present operational feasibility, commercial viability, or ability to accommodate cargo volumes comparable to those passing through the Strait of Hormuz.

The proposed Gulf–Levant–Europe corridor should therefore be understood as a prospective, scenario-based network configuration rather than a confirmed transport alternative. The present study does not independently verify route-specific infrastructure readiness, border and customs procedures, political and security conditions, legal compatibility, insurance availability and costs, cargo-handling capability, or required capital investment. These limitations are particularly important because parts of the proposed network extend through geopolitically sensitive and post-conflict areas. Future research should undertake a comprehensive route-level feasibility assessment supported by longitudinal evidence on cargo flows, infrastructure investment, border-crossing performance, route utilization, security conditions, and commercial costs. Such evidence would be necessary to determine whether an actual reconfiguration of trade routes is occurring, assess the factors driving it, and establish whether the proposed corridor could function as an operationally and commercially viable transport alternative.

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Footnotes

Edited by: Kara Reynolds, American University, United States

Reviewed by: Małgorzata Krystyna Kamola-Cieślik, University of Szczecin, Poland

Huanyu Ren, Jimei University, China