Assessing Logistic and Railway Readiness in the NELBEC: A Composite Index for Belt and Road Integration

Abstract

The Belt and Road Initiative (BRI), launched in 2013, is one of the most ambitious global projects of the 21st century, aiming to enhance connectivity and trade between Asia and Europe. Within this framework, the New Eurasia Land Bridge Economic Corridor (NELBEC) stands out as a key transcontinental route where railway logistics plays a central role. However, few studies have systematically assessed the readiness of participating countries to integrate effectively into this corridor. This study aims to develop and apply a composite index to evaluate and compare the logistics and railway readiness of Russia, Belarus, Kazakhstan, and Poland within the NELBEC. The methodology integrates the World Bank’s Logistics Performance Index (LPI) with railway-specific indicators derived from academic literature and institutional datasets. All indicators were normalized, weighted through expert consultation, and aggregated into two dimensions: logistics readiness and railway readiness. The results show that Russia exhibits the highest overall readiness, driven by strong railway capacity but weaker logistics performance, followed by Poland, with advanced infrastructure and efficient customs procedures. Kazakhstan and Belarus present lower readiness levels due to limited terminal capacity and outdated infrastructure. The findings offer policymakers and regional planners a tool to help them make decisions, identify infrastructure bottlenecks, prioritize investments, and design policies that will lead to a more sustainable integration into the BRI.

1. Introduction

The Belt and Road Initiative (BRI), announced by Chinese President Xi Jinping in 2013 and officially launched in 2015, has emerged as one of the most ambitious infrastructure and development programs of the 21st century [1]. Designed to strengthen connectivity between Asia, Europe, and Africa, the BRI combines maritime and land corridors that aim to foster regional integration, stimulate economic growth, and facilitate global trade [2]. Beyond its economic objectives, the BRI also represents a strategic geopolitical project, consolidating China’s influence across Eurasia and promoting long-term partnerships with participating countries [3].

At its core, the BRI is structured around two main components: the Silk Road Economic Belt, which encompasses land-based transport routes, and the 21st Century Maritime Silk Road, focused on sea lanes of trade [4,5]. These two pillars function in synergy, enabling China to consolidate its presence in key global trade corridors and secure access to markets across Eurasia and beyond [6]. By 2020, more than 138 countries and 30 international organizations had signed cooperation agreements with China under the BRI framework, reflecting the initiative’s broad international appeal [5,7].

Among the six economic corridors defined within the BRI, the New Eurasia Land Bridge Economic Corridor (NELBEC) is one of the most strategically important. Unlike maritime routes, NELBEC relies predominantly on railway networks to connect China with Europe through Central Asia and Eastern Europe [8,9,10]. The corridor passes through key transit countries such as Russia, Kazakhstan, Belarus, and Poland, making them critical nodes in the efficiency and sustainability of Eurasian connectivity.

The corridor traverses from Russia’s Far East and Siberia to the Urals and Central Russia, improving transport connectivity and economic output as it moves westward, then connecting East Asia to Europe [11]. Kazakhstan is a key transit hub in Central Asia, focusing on international investment and integration projects to enhance its transport infrastructure and connectivity [12]. Belarus along with Russia and Kazakhstan benefits from increased economic integration and trade facilitation through the Eurasian Economic Union (EEU), enhancing regional stability and economic growth, which supports the broader goals of the NELBEC [13]. Poland’s strategic importance lies in its role as a gateway to the European Union (EU) and its involvement in projects like the Rail Baltica enhances cross-border connectivity, making it a crucial link between the NELBEC and the rest of the European logistics networks [12,14]. Given its role in reducing transit times and offering a cost-effective alternative to maritime transport, NELBEC has become a focal point for policymakers and scholars seeking to understand the dynamics of the BRI and its potential impacts on regional and global trade.

Although the BRI has been widely studied from economic, political, and infrastructural perspectives, the literature addressing logistics and railway readiness remains fragmented. Many authors have analyzed the BRI in terms of barriers to trade, improvements in transport infrastructure, or its broader economic implications [6,15,16]. For example, Zeybek [17] highlighted the role of railway transport as a faster alternative to maritime routes, while Uygun and Ahsan [1] and Pató et al. [18] emphasized the growing importance of rail freight in linking Asia and Europe. Other studies have assessed the potential of specific the six BRI economic corridors [9], and apply a utility function composed of independent variables such as transportation cost, environmental impact, transit time, mode reliability, and mode safety, positioning rail transport as one of the means with the lowest carbon emissions, lowest cost, and highest safety in the event of cargo accidents [8].

Despite these contributions, few studies have developed integrated frameworks to measure the preparedness of key nodes in the BRI. Most existing analyses rely heavily on the World Bank’s LPI, which, although widely used, does not specifically capture railway-related dimensions critical to the NELBEC [19,20]. As a result, there is a gap in the literature regarding how to evaluate the combined logistic and railway readiness of countries that play strategic roles in transcontinental corridors. Addressing this gap is particularly important given the increasing reliance on rail transport for long-distance trade between China and Europe, and the potential bottlenecks that may arise at border-crossing nodes such as Belarus–Poland [6].

This study aims to address the identified research gap by proposing a new methodological framework to evaluate the readiness of countries for integration into the BRI through NELBEC. Specifically, the research develops a composite index that combines the World Bank’s LPI with railway-related indicators, such as infrastructure quality, border connectivity, terminal capacity, and customs procedures. By integrating these dimensions, the index provides a multidimensional measure of logistics and railway preparedness, tailored to the specific requirements of rail-based corridors.

Therefore, the contribution of this study is twofold. From a theoretical perspective, it introduces a novel index that advances the measurement of logistic readiness in the BRI context, going beyond existing single-source indicators. From a practical perspective, the findings offer actionable insights for policymakers, international organizations, and private investors by identifying bottlenecks and priority areas for infrastructure and institutional improvements. Ultimately, the study enhances understanding of how Eurasian countries can prepare more effectively for participation in the BRI and strengthen sustainable transcontinental trade integration.

2. Literature Review

This section reviews empirical and conceptual studies that focus on the role of BRI corridors in facilitating Eurasian connectivity and modernizing logistics. It emphasizes the methodological gaps in integrating rail-specific indicators and highlights key contributions to the measurement of logistics performance.

2.1. Studies on the Belt and Road Initiative and Economic Corridor Development

Since its launch in 2013, the BRI has attracted growing academic interest across multiple disciplines, including international trade, geopolitics, and infrastructure studies. Research has emphasized its transformative potential for enhancing Eurasian connectivity and stimulating regional economic growth. Chen et al. [5] highlighted that logistics and transport represent more than 40% of the studies published on the BRI between 2013 and 2019, reflecting the centrality of infrastructure and supply chain efficiency in the initiative.

A significant portion of the literature has examined the role of economic corridors as the backbone of the BRI. Authors such as Uygun and Ahsan [1] have underlined the increasing reliance on rail freight, noting that railways serve as the most cost-effective compromise between speed and capacity when compared to maritime and air transport. Empirical studies have further shown that railway transport can cut delivery times by more than half relative to maritime shipping, thereby reinforcing its attractiveness for China–Europe trade flows [15,17].

Attention has also been directed to the strategic role of specific corridors, for instance, Sheng and Nascimento [9] evaluated the relative performance of the six economic corridors of the BRI (NELBEC, CMREC, CIPEC, CCWAEC, CPEC, BCIMEC) identifying many underdeveloped countries need significant investments to improve their precarious infrastructure, including non-uniform railway technical standards. Wen et al. [8] demonstrated the remarkable advantages of the six economic corridors of the BRI over the traditional ocean route and their heterogeneous impacts on different regions of China. Other works stress the critical importance of border-crossing points, such as Brest–Małaszewicze between Belarus and Poland, which frequently act as bottlenecks in transcontinental logistics chains [6]. These studies demonstrate that the BRI is not merely an infrastructure program but a complex system of corridors and nodes where logistics performance determines the initiative’s overall viability. However, while prior research has described infrastructural developments and logistical challenges, few studies have attempted to measure systematically the readiness of countries along key corridors such as NELBEC.

2.2. Logistics Performance Indices and Rail-Specific Indicators

One of the most widely used tools for assessing logistics performance at the country level is the World Bank’s LPI. The LPI provides a comparative evaluation across more than 150 countries based on six key dimensions, which are customs efficiency, infrastructure quality, international shipments, logistics competence, tracking and tracing, and timeliness [21]. While the index has become a standard reference for analyzing supply chain capabilities, it is primarily designed to capture broad trends in logistics rather than corridor-specific dynamics.

Several authors have highlighted the strengths and weaknesses of the LPI when applied to the BRI. Bentyn [22] compared the LPI evolution of Kazakhstan, Russia, Belarus, and Poland, showing significant improvements in some cases due to Chinese investments. However, this study also noted that the LPI fails to account for critical corridor-specific variables such as railway infrastructure quality or border-crossing efficiency. Similarly, Nazarko et al. [23] argued that while the LPI reflects general logistics development, it overlooks the unique challenges faced by countries in Eastern Europe and Central Asia that are integral to the BRI.

Other studies have pointed out that relying exclusively on the LPI may obscure the realities of transcontinental trade. Zhang et al. [19] emphasized the importance of identifying and measuring the role of strategic nodes in the China Railway Express, noting that traditional indices are insufficient to capture bottlenecks and node-specific readiness. Yu et al. [20] further argued that indicators of customs harmonization, terminal capacity, and digitalization are essential to understanding railway logistics performance but remain absent from conventional indices. While the LPI and related measures provide valuable insights, they are inadequate for analyzing the integrated logistics and railway readiness required for corridors like NELBEC. This limitation underscores the need for new multidimensional frameworks that combine logistics performance with railway-specific indicators to evaluate the true preparedness of countries for participation in the BRI.

Table 1. Summary of previous research on logistics performance and railway readiness within the BRI.

Author	Main Focus	Methods	Key Findings	Gaps/Limitations
[22]	Evolution of LPI in BRI countries such as Kazakhstan, Russia, Belarus, Poland	Longitudinal analysis of World Bank LPI	Showed logistics improvement driven by Chinese investment	LPI alone does not reflect railway or cross-border performance
[23]	Comparative analysis of Eastern European BRI countries	LPI-based comparative study	Highlighted Poland’s high logistics capacity	LPI lacks corridor- and railway-specific indicators
[8]	Impact of six BRI economic corridors on China–Europe and advantages over the traditional ocean route	Route Utility Function	Demonstrated advantages of BRI rail corridors over maritime routes	Focused mainly on Chinese regions
[15]	Cooperation in customs and logistics between China and Russia	Qualitative and quantitative indicators, official statistical data of Russia and China and findings of previous studies.	Showed steady trend for integration of Russian and Chinese crossborder infrastructure, and benefits of customs digitalization and harmonization	Lack of systematic weighting and composite index
[6]	Barriers to BRI logistics integration	Qualitative analysis of institutional and infrastructure factors	Identified cross-border inefficiencies and technical incompatibilities	Lack of measurable indicators for readiness or systematic weighting
[19]	Importance of nodes in China Railway Express	Multi-attribute decision model (MADM) to rank inland and seaport nodes	Identified Moscow as the first in the overall node’s importance and suggests expanding the Maritime Silk Route from coastal regions to the whole Silk Road Economic Belt through the rail–sea intermodal transport	Focused only on node-level performance; no aggregated or weighted country-level readiness index
[24]	Efficiency of intermodal (maritime terminal and the railway terminal) container terminals	Two-echelon dual-channel model	Found capacity and accumulation issues in China Railway Express terminals according to the intermodal transportation demand.	Limited to terminal-level modeling
[9]	Performance of six BRI economic corridors	Comparative analysis of corridor development	Identified infrastructure deficits and inconsistent rail standards	No specific readiness evaluation or weighting methodology
[1]	Analysis of the Belt and Road railway network and corridor efficiency	Network analysis of BRI rail routes	Highlighted the importance of railway freight for cost-effective transcontinental transport	Lack of integrated measures combining logistics and railway indicators
[5]	Review of transport and logistics research on the BRI	Systematic literature review	Found that transport and logistics dominate BRI-related research (more than 40% of studies)	No quantitative framework for readiness assessment
[25]	Location of logistics distribution centers along BRI	Explorative location analysis based on qualitative and quantitative facility location factors	Identified strategic hubs for global logistics distribution centers	No composite framework for corridor performance
[20]	Consolidation centers under the BRI to reduce the high logistics costs among the different transportation modes.	CRITIC method, TOPSIS method and Grey Relational Analysis	Recommendation of eight Chinese cities as consolidation centers for the integration of different transportation modes	Focused on the location of consolidation centers rather than on logistics and railway performance.

summarizes the main contributions of previous studies addressing logistics and railway performance within the BRI. These works collectively demonstrate the growing relevance of railway connectivity for Eurasian trade but also reveal methodological gaps. Most studies rely on general indices such as the World Bank’s LPI or on qualitative analyses of infrastructure, with limited attention to integrated, multidimensional measures that jointly evaluate logistics and railway readiness.

Given the limitations of existing indices, scholars have increasingly emphasized the need for more tailored and multidimensional approaches to evaluate logistics performance in the context of the BRI. Composite indices, which combine multiple indicators into a single measure, have been proposed as a robust tool for capturing the complex realities of international trade and transport systems [26,27]. Such indices allow researchers to integrate variables from different domains, including infrastructure, policy, and operational efficiency, offering a more comprehensive perspective than single-source metrics [28,29].

In the case of NELBEC, the development of a composite index is particularly relevant. The corridor’s efficiency depends not only on general logistics capabilities but also on specific railway-related factors such as the condition and length of rail networks, border connectivity, terminal capacity, and customs harmonization. Studies have demonstrated that bottlenecks at border points, insufficient terminal infrastructure, and lack of digitalized customs processes can significantly undermine the corridor’s effectiveness [6,20,24]. Similarly, Uygun and Ahsan [1] and Lee et al. [25] have underlined that the competitiveness of NELBEC compared to maritime transport depends largely on the ability of railway nodes to handle high volumes of cargo efficiently.

A composite index that integrates these elements would not only provide a more accurate assessment of readiness but also serve as a decision-making tool for policymakers and investors. Zhang et al. [19] emphasized the importance of focusing on critical nodes in the China Railway Express, which play a decisive role in determining the overall performance of transcontinental rail logistics. By capturing both logistics and railway dimensions, a customized index can highlight country-specific strengths and weaknesses, identify priority areas for investment, and promote greater alignment with the objectives of the BRI.

3. Materials and Methods

To assess the logistic and railway readiness of countries along NELBEC, this study employs a composite index methodology. Composite indices are widely used to summarize multidimensional phenomena into a single measure, allowing for the integration of diverse variables in a structured and comparable framework [29]. In this research, the index was designed to capture both general logistics performance and railway-specific dimensions that are critical for the BRI. The construction of the index followed four main stages: indicator selection, normalization, weighting, and aggregation.

3.1. Indicator Selection

We have chosen to apply the indicators offered by the World Bank’s Logistics Performance Index to make up the composite index. We have also adapted specific indicators to the needs of this study using proxy indicators, which allow for an adequate approximation of the variable being analyzed when data is scarce [30]. This is useful in the context of the BRI, where railway infrastructure and logistics have unique characteristics. Using composite or proxy indicators offers flexibility and allows us to capture the multidimensionality of the phenomena under study. In this case, we are studying the capacity for integration of countries in the BRI.

The final set of indicators was determined by the research team according to their relevance, complementarity, and measurability. Indicators were selected to ensure a comprehensive assessment of both logistics and railway readiness, avoiding redundancy while capturing distinct aspects of corridor integration. Furthermore, data availability and comparability across the four selected countries were essential criteria, ensuring that the indicators could be measured consistently over time and across contexts. Indicators were chosen from two complementary sources, which are the World Bank’s LPI and railway-specific indicators from institutional reports and academic literature. By combining LPI indicators with railway-specific measures, the dataset enabled a multidimensional evaluation of readiness.

The LPI is a biannual index covering over 150 countries and evaluating logistics performance across six key dimensions related to customs efficiency, infrastructure quality, international shipments, logistics competence, tracking and tracing, and timeliness. Given its widespread use and methodological rigor, the LPI provided the baseline indicators for the logistics dimension of the index. Although limited in scope regarding railway-specific aspects, it remains the most recognized benchmark for cross-country logistics comparisons [21,22].

Table 2. Variables and indicators of the World Bank’s LPI.

LPI Variable	Description	Source
Competence and quality of logistics services	Measures the quality and competitiveness of logistics services provided by private sector actors (e.g., customs brokers, freight forwarders, transport operators) and evaluates the effectiveness of public institutions managing border procedures. It also reflects governance quality, regulatory environment, and overall business climate affecting logistics services.	[21,31].
Ease of arranging competitively priced shipments	Assesses a country’s ability to coordinate international shipments at competitive prices. It includes costs such as port charges, inland transportation, freight forwarding, and warehousing, which directly affect the customs value of exported goods.	[19,32,33]
Timeliness of shipments	Evaluates the frequency and reliability of shipments arriving on schedule. It reflects the country’s capacity to ensure timely delivery and consistency in freight movements.	[34]
Quality of trade and transport infrastructure	Examines the physical infrastructure used for goods transport (roads, ports, railways, and airports) and the quality of information and communication technologies supporting trade logistics.	[2,35]
Customs clearance efficiency	Measures the efficiency and transparency of the customs process, including inspection times, electronic clearance procedures, and the transparency of documentation and regulations.	[36]
Tracking and tracing ability	Captures the ease with which shipments can be tracked and traced through different logistics systems and digital platforms. It reflects the technological integration of logistics networks.	[14]

presents the corresponding indicators adopted in this study based on the LPI.

Railway-specific indicators were incorporated from institutional reports (e.g., OECD, International Union of Railways, and national transport ministries) and academic literature, including rail network length and condition, terminal capacity, customs digitalization, and border connectivity. In this regard, logistics development, including railway development, is a key aspect of the new Silk Road that must be evaluated [1,37]. Guo et al. [24] and Uygun and Ahsan [1] examined the installed capacity of various rail ports in countries participating in the New Silk Road, emphasizing the importance of identifying bottlenecks and potential alternative routes. Furthermore, Nitsche [6] and Chen [15] identify and mention customs procedures as variables. Likewise, Zhang et al. [19] and Yu et al. [20] consider it relevant to evaluate the efficiency of the cross-border nodes or edges of different countries belonging to the New Silk Road. Together, these indicators directly affect the capacity of countries to serve as effective transit hubs within NELBEC and capture the multidimensional nature of readiness, combining general logistics with corridor-specific railway variables.

Table 3. Railway-Specific Indicators for Assessing Readiness along NELBEC.

Variable	Description	Indicator(s)	Description
Railway Development	It reflects the overall condition of the railways, which have the capacity to handle the high volume of goods expected to be transported through the NELBEC economic corridor [14,25].	Railway network length and condition	Evaluates the percentage of operational railway tracks relative to total network length, reflecting infrastructure capacity and efficiency for freight transport [6,38].
		Chinese FDI inflows in rail infrastructure	The proportion of Chinese foreign direct investment (FDI) in railway infrastructure, which enhances intermodal connectivity and logistics competitiveness [20,39].
Terminal Capacity	This parameterizes the installed capacity of railway logistics centers and the time required for customs clearance. This is important because inadequate logistics infrastructure will not be able to support the high volume of traffic at border control points [1,24,25].	Number of available freight wagons	Quantifies terminal capacity through wagon availability, reflecting the ability of national networks to support large freight volumes [38,40].
		Volume of goods transported by rail	Quantifies the total volume of goods handled by rail terminals, reflecting the ability of minimize congestion at critical nodes and meet the transport demand [41].
Customs Procedures	It aims to determine the percentage of digitization in customs procedures and customs harmonization among NELBEC member countries since the implementation of the BRI [15,20].	Customs digitalization	Measures the adoption of digital platforms for customs clearance (e.g., e-declarations, online payments, automated permits). It enhances transparency, reduce clearance times [42].
		Customs harmonization	Measures the degree of harmonization of customs rules among NELBEC countries. Promotes interoperability between national systems [19].
Border Connectivity	It emphasizes the potential for rail transportation to become one of the most efficient modes of transportation in the BRI area, particularly for long-distance freight [4,43].	Number of railway border-crossing nodes	Measures the total number of railway border-crossing nodes or control points between NELBEC countries, indicating the ease of cargo interchange and cross-border logistics fluidity. Higher connectivity reduces delays and improves trade flow efficiency [2,19].

summarizes the railway-specific indicators incorporated into the composite index, to complement the LPI-based logistics dimension.

The logistics indicators derived from the World Bank’s LPI were complemented with railway-specific data obtained from institutional sources such as The World Bank, PKP Polskie Linie Kolejowe S.A., Belarusian Railway, NC KTZ JSC, and Russian Railways, which provided detailed national-level statistics on rail infrastructure, network length, and operational capacity. The American Enterprise Institute was consulted for information on Chinese FDI inflows in rail infrastructure. Additional datasets were extracted from global repositories including The World Bank, Open Railway Map, and Mordor Intelligence, which offered comparative metrics on freight transport performance, border connectivity, terminal capacity and infrastructure conditions. Complementary information regarding customs digitalization, regulatory harmonization and cross-border procedures was gathered from the United Nations, the EEU, the EU, and the Ministry of Foreign Affairs of the Russian Federation. These sources ensured data consistency and comparability across the four case countries (Russia, Belarus, Kazakhstan, and Poland), while capturing both macro-level logistics trends and corridor-specific railway performance essential for the NELBEC assessment.

Figure 1 provides a visual representation of the proposed Railway Logistics Readiness Index (RLRI), which incorporates the six core LPI variables and the four key dimensions of the Railway Index into a unified composite framework, including specific indicators. This composite index captures both systemic logistics performance and railway-specific readiness.

This framework is used to construct the RLRI that evaluates NELBEC countries’ preparation for integration into the BRI, providing a comprehensive and measurable framework that captures both logistical efficiency and railway performance, forming the basis for composite index construction.

3.2. Normalization

Because the selected indicators are measured in different units (e.g., kilometers, percentages, categorical scores), a min–max rescaling method was applied to standardize values within the [0, 1] range [44]. This ensured comparability across variables while preserving their relative magnitudes [45]. The normalization process transformed each variable into a dimensionless value ranging from 0 to 1, where 1 represents the best observed performance and 0 the worst. Two normalization formulas were applied, depending on whether the indicator had a positive or negative relationship with readiness.

Equation (1) is used for a positive indicator and Equation (2) is used to represent a negative indicator, where $X_{ij}$ represents the original value of indicator i for country j; $\mathrm{m}\mathrm{i}\mathrm{n}\left(x_i\right)$ and $\mathrm{m}\mathrm{a}\mathrm{x}\left(x_i\right)$ are the minimum and maximum observed values of indicator i across all countries; and $Z_{ij}$ is the normalized value of indicator i for country j, rescaled between 0 and 100. This normalization approach ensures that all indicators contribute proportionally to the composite index, preventing those with larger numerical scales from dominating the final results.

$$z_{ij}={\displaystyle \frac{x_{ij}-\mathrm{m}\mathrm{i}\mathrm{n}\left(x_i\right)}{\mathrm{m}\mathrm{a}\mathrm{x}\left(x_i\right)-\mathrm{m}\mathrm{i}\mathrm{n}\left(x_i\right)}}\times 100$$

(1)

$$z_{ij}=1-{\displaystyle \frac{x_{ij}-\min \left(x_i\right)}{\max \left(x_i\right)-\min \left(x_i\right)}}\times 100$$

(2)

In this study, all variables were found to have a positive relationship with the RLRI, meaning that higher values indicate better performance in logistics and railway readiness. Therefore, the normalization process employed Equation (1) for all indicators. To compute normalized values, it was first necessary to define the minimum and maximum thresholds for each indicator, as shown in

Table 4. Minimum and maximum thresholds used for indicator normalization.

Indicator	Minimum Threshold	Maximum Threshold
Competence and quality of logistics services	1	5
Ease of arranging competitively priced shipments	1	5
Timeliness of shipments	1	5
Quality of trade and transport infrastructure	1	5
Customs clearance efficiency	1	5
Tracking and tracing ability	1	5
Railway network length and condition	0	100
Chinese FDI inflows in rail infrastructure	0	15
Number of available freight wagons	0	100
Volume of goods transported by rail	0	3,036,292
Customs digitalization	0	100
Customs harmonization	0	100
Number of railway border-crossing nodes	0	27

. The minimum thresholds correspond to the lowest values in each indicator’s original measurement scale. For qualitative indicators derived from the World Bank’s LPI, the minimum score is 1 (very low performance) and the maximum is 5 (very high performance). For quantitative indicators, the minimum threshold of 0 indicates the absence of performance or measurable value in the respective variable. These thresholds represent the empirical range of observed data across the four case countries and serve as reference points for rescaling the indicators between 0 and 100.

The normalization process effectively eliminated scale bias, allowing each variable to contribute proportionally to the RLRI, allowing for consistent aggregation across dimensions and countries.

3.3. Weighting

To reflect the relative importance of each indicator within the RLRI, weights were determined using the Budget Allocation Point (BAP) approach. This method is based on expert judgment, allowing specialists to express their informed opinions regarding the significance of individual dimensions, variables, and indicators that compose the index [46]. Experts in logistics, geopolitics, and research methodology were consulted through a structured survey. Each expert was provided with a hypothetical “budget” of 100 points to distribute among the components of the RLRI, according to their professional experience and perception of the relative importance of each element.

The process was conducted in three hierarchical stages. Experts first distributed 100 points between the two primary dimensions of the RLRI, which are LPI and Railway Readiness. Within each dimension, another allocation of 100 points was made among the corresponding variables. Finally, within each variable of the railway index, experts assigned 100 points among the specific indicators constituting that variable. Each expert completed the survey independently to prevent group influence and minimize cognitive or social bias. Participants were also encouraged to provide written justifications for their allocations, ensuring transparency and interpretability in the weighting rationale. Once the surveys were collected, the assigned weights were averaged across experts, yielding the final set of weights for each dimension, variable, and indicator.

The final weighting structure, summarized in

Table 5. Final weights assigned to each dimension, variable and indicator.

Dimension (Level 1)	Weight (%)	Variable/Indicator (Level 2)	Weight (%)	Indicator (Level 3)	Weight (%)
LPI	60.0%	Competence and quality of logistics services	13.90%	-	-
		Ease of arranging competitively priced shipments	15.60%	-	-
		Timeliness of shipments	22.20%	-	-
		Quality of trade and transport infrastructure	18.90%	-	-
		Customs clearance efficiency	17.20%	-	-
		Tracking and tracing ability	12.20%	-	-
Railway Index	40.0%	Railway Development	25.00%	Railway network length and condition	70.00%
				Chinese FDI inflows in rail infrastructure	30.00%
		Terminal Capacity	38.30%	Number of available freight wagons	36.70%
				Volume of goods transported by rail	63.30%
		Customs Procedures	18.30%	Customs digitalization	51.70%
				Customs harmonization	48.30%
		Border Connectivity	18.30%	Number of railway border-crossing nodes	100%

, presents the distribution of weights across the two principal dimensions and their respective variables and indicators. Expert assessments revealed that the LPI dimension was assigned to a higher overall weight (60%) than the Railway Index dimension (40%), highlighting the experts’ consensus that efficient logistics systems remain the backbone of NELBEC’s operational success. This prioritization reflects the understanding that improvements in logistics infrastructure, customs performance, and transport coordination are fundamental enablers for the effective integration of railway networks within the Belt and Road Initiative framework.

Within the LPI dimension, the variables receiving the highest weights were Timeliness of Shipments (22.2%), Quality of Trade and Transport Infrastructure (18.9%), and Customs Clearance Efficiency (17.2%). These results suggest that experts perceive punctual delivery, infrastructure quality, and border management efficiency as the most critical factors driving overall logistics readiness in the Eurasian corridor. Such emphasis aligns with previous studies identifying infrastructure modernization and time reliability as decisive contributors to competitiveness and supply chain resilience [1,6,24].

Conversely, within the Railway Index dimension, the variable with the greatest influence was Terminal Capacity (38.3%), followed by Railway Development (25%), while Customs Procedures and Border Connectivity each accounted for 18.3%. At the indicator level, the most heavily weighted components were Railway Network Length and Condition (70%) under Railway Development, Volume of Goods Transported by Rail (63.3%) under Terminal Capacity, and Customs Digitalization (51.7%) under Customs Procedures. These results indicate that experts attribute high strategic value to the modernization and operational capacity of railway infrastructure, as well as to the digitalization and harmonization of customs processes, which are key elements for reducing border delays and enhancing corridor interoperability.

3.4. Aggregation

The aggregation of indicators into a composite index involves the systematic combination of multiple normalized and weighted variables into a single representative score. This procedure is fundamental for evaluating complex phenomena in a summarized way, allowing for comparisons among countries and the identification of specific areas for improvement [26]. In the present study, the proposed RLRI integrates key indicators reflecting critical aspects of logistics and railway development. The first stage of the aggregation process consists of computing sub-indices for each dimension (logistics readiness and railway readiness). This is achieved by averaging the normalized and weighted indicators belonging to each dimension, as represented by Equation (3), where $S_D$ represents the sub-index value for dimension D (either logistics or railway readiness); $w_i^D$ is the normalized weight assigned to indicator i within dimension D (such that $\sum w_i^D=1$); $I_i^D$ is the normalized value of indicator i within dimension D; and $n_D$ is the number of indicators included in dimension D. Once the sub-indices for both dimensions were obtained, they were combined into the final composite index using the aggregation formula expressed in Equation (4), where $\mathrm{R}\mathrm{L}\mathrm{R}\mathrm{I}$ represents the final composite index value for each country; $w_D$ is the weight assigned to each dimension D; and $M$ is total number of dimensions.

$$\begin{array}{cccc}& S_D={\displaystyle \sum _{i=1}^{n_D}}{w}_i^D\times I_i^D& & \end{array}$$

(3)

$$\mathrm{R}\mathrm{L}\mathrm{R}\mathrm{I}=\sum _{D=1}^M{w}_D\times S_D$$

(4)

This aggregation process produces a final index score ranging from 0 to 100, where higher values represent greater levels of logistical and railway readiness. The results allow both cross-country comparison and dimension-specific interpretation, supporting an in-depth understanding of each country’s strengths and weaknesses within NELBEC. To facilitate interpretation, the aggregated results were classified into five performance levels shown int

Table 6. Scale for measuring performance based on the RLRI.

Performance Level	Score Range	Interpretation
Optimal Performance	81–100	Outstanding logistical and infrastructural readiness
Advanced Performance	61–80	High degree of integration with minor improvement needs
Moderate Performance	41–60	Adequate readiness but several improvement areas remain
Deficient Performance	21–40	Significant gaps in logistics and infrastructure development
Critical Performance	0–20	Very low readiness, severely limiting integration into the BRI

.

The five-level classification (Critical, Deficient, Moderate, Advanced, and Optimal) was defined by the authors following a structure comparable to a five-point Likert scale, which facilitates intuitive interpretation and comparability. Each interval covers 20 score points, ensuring uniform distribution and ease of use for policy evaluation. While nonlinear transformations such as logarithmic scaling were considered, a linear classification was preferred to maintain simplicity and interpretability of the index results.

3.5. Case Study Application: Russia, Belarus, Kazakhstan, and Poland

The empirical application of the RLRI focused on four countries that serve as critical transit nodes along the NELBEC, which are Russia, Belarus, Kazakhstan, and Poland. As shown in Figure 2, these countries serve as strategic nodes for Eurasian connectivity, yet they differ significantly in their levels of infrastructure development, customs efficiency, and integration into global supply chains. Applying the RLRI to these cases allows for a comparative assessment of strengths and weaknesses, highlighting where investments and policy reforms are most urgently needed. These countries were selected based on three main criteria: geostrategic position, infrastructure and logistical relevance, and comparative assessment.

All four countries lie directly on the main railway route linking China to Europe. Kazakhstan serves as China’s primary gateway into Central Asia; Russia provides the longest transcontinental segment of the corridor; Belarus represents a key border-crossing state before entry into the EU; and Poland acts as the first EU member state and terminal hub for China–Europe trains [6]. Each country has invested heavily in transport infrastructure in recent decades, although with varying degrees of modernization and efficiency. Russia and Kazakhstan rely on extensive but unevenly modernized networks; Belarus functions as a strategic bottleneck at the Brest–Małaszewicze crossing; and Poland has leveraged EU integration to modernize its logistics infrastructure and improve customs processes [15,22].

By applying the index to these cases, it was possible to evaluate relative strengths and weaknesses. The normalization and weighting procedures produced readiness scores for each dimension (logistics and railway), which were then aggregated into an overall index value (RLRI) for each country. This allowed for both cross-country comparison and intra-country analysis of performance gaps across the two dimensions. The single composite score, expressed on a 0–100 scale, provided the empirical basis for the results and discussion presented in the following sections.

4. Results

The RLRI results provide a comparative overview of the logistics and railway readiness levels of Russia, Belarus, Kazakhstan, and Poland. As shown in Figure 3, substantial variation exists among the four countries, underscoring structural asymmetries in logistics performance, railway development, and customs modernization within the NELBEC. The findings reveal that Russia achieved the highest readiness score (54.6), followed by Poland (49.8) and Kazakhstan (41.7), while Belarus (36.5) exhibited lower levels of readiness. According to the performance classification, Russia, Poland and Kazakhstan fall within the “moderate performance” range (41–60), whereas Belarus is categorized as “deficient performance” (21–40). It highlights the predominance of the railway dimension in Russia’s readiness profile.

Breaking down the composite index into its two main dimensions (LPI and Railway Index) and respective indicators (see Figure 4, Figure 5 and Figure 6) reveals distinct national patterns. Poland leads the logistics dimension, obtaining a score of 64.8, significantly above Belarus (43.6), Kazakhstan (42.2), and Russia (39.8). Poland’s superior logistics readiness is supported by its high-quality trade and transport infrastructure, efficient customs clearance, and strong integration into European supply chains. These results align with prior research emphasizing Poland’s pivotal role as the EU’s eastern logistics hub [1,6]. In contrast, Russia dominates the railway dimension with a score of 76.7, far exceeding Kazakhstan (41.1), Belarus (25.9), and Poland (27.2). This performance reflects Russia’s extensive and well-maintained rail network, large freight capacity, and progress in customs digitalization under the EEU framework. Nonetheless, Russia’s relatively weak logistics performance, particularly in customs efficiency and tracking systems, continues to constrain its overall integration potential.

Kazakhstan, positioned third overall, demonstrates balanced but moderate performance in both dimensions (LPI: 42.2; Railway Index: 41.1). The country benefits from substantial Chinese investment in rail infrastructure and its strategic geographic position as a gateway to Central Asia. However, limited terminal capacity (8.7) and slow progress in digital customs harmonization hinder its transition toward advanced performance levels. Belarus exhibits the lowest composite score, driven by severe limitations in railway capacity (25.9) and persistent bottlenecks at the Brest–Małaszewicze border crossing. Despite moderate logistics indicators such as competence of logistics services (42.5) and timeliness of shipments (52.5), Belarus’s infrastructure and customs challenges significantly reduce its readiness for deeper integration into the BRI.

5. Discussion

5.1. Country-Specific Analysis

To identify the main strengths and weaknesses in logistics and railway readiness across the NELBEC, a country-level analysis was conducted for Poland, Russia, Kazakhstan, and Belarus.

5.1.1. Russia

Russia demonstrated the highest performance in the Railway Index among the four countries, confirming its central role in transcontinental freight transport. The country’s railway development variable recorded exceptional results (86.0), reflecting that over 95% of its total railway lines are operational. This capacity minimizes the risk of congestion and positions Russia as the most structurally prepared participant within NELBEC. Similarly, the country obtained high scores in terminal capacity (84.5) due to the availability of freight wagons and the volume of goods transported by rail. Within customs procedures (76.1), Russia benefits from membership in the EEU, which facilitates preferential trade agreements and efficient border procedures. Border connectivity (48.0), while relatively lower, remains sufficient for large-scale transit operations across Eurasia.

However, Russia’s logistics performance dimension reveals clear weaknesses. With an overall LPI score of 39.8, the country ranks 88th globally in the World Bank index, reflecting systemic inefficiencies in customs clearance (35.0) and tracking systems (37.5). Despite moderate performance in timeliness (47.5) and infrastructure quality (42.5), Russia struggles with shipment coordination at competitive prices (32.5). These deficiencies raise logistics costs and reduce competitiveness, particularly in western export routes.

Therefore, Russia’s overall readiness (RLRI = 54.5) is driven by railway excellence but constrained by logistics inefficiencies. Strategic priorities should include improving border connectivity and nodes, reducing administrative costs, as well as strengthening trade relations with the EU to enhance cross-border interoperability.

5.1.2. Poland

Poland emerged as the top performer in the LPI, scoring 64.8 and ranking 33rd globally. This performance consolidates its reputation as the European gateway of the NELBEC. Poland’s logistics strength lies in timeliness of shipments (72.5), customs efficiency (60.0), and infrastructure quality (62.5), all within the “advanced performance” category. Its tracking and tracing ability (70.0) further reinforces its integration into EU digital systems.

Nevertheless, Poland’s railway dimension presents structural challenges. Despite moderate success in customs procedures (58.3) and ongoing modernization at Małaszewicze terminal, the country obtained low scores in railway development (50.3) and particularly in terminal capacity (3.1). The small number of available freight wagons and limited border connectivity (15.0) indicate capacity constraints that hinder its potential role as a major transcontinental hub. Poland’s RLRI score (49.7) reflects a balanced, though uneven, readiness, since it is advanced in logistics but weak in railway infrastructure. Policy recommendations include expanding wagon fleets, improving intermodal connectivity with eastern partners, and investing in rail capacity to complement its strong logistics base.

5.1.3. Kazakhstan

Kazakhstan ranked third in the overall index (41.7), reflecting moderate readiness with mixed performance across dimensions. In the LPI, Kazakhstan scored 42.2, placing it 84th globally. The country performed best in timeliness (47.5) and infrastructure quality (37.5) but scored lower in tracking systems (45.0) and shipment coordination (40.0). These results indicate moderate logistics capabilities but persistent inefficiencies in customs transparency and process standardization.

In the railway dimension, Kazakhstan achieved relatively strong results in railway development (81.2) and customs procedures (76.4), reflecting Chinese investment and its role as China’s western gateway. However, terminal capacity remains a critical weakness (8.7), highlighting the shortage of freight wagons and insufficient handling capacity at major hubs such as Khorgos. Border connectivity (19.0) also limits throughput efficiency. Consequently, Kazakhstan’s position between “moderate” and “advanced” performance suggests untapped potential. To strengthen readiness, the country should focus on expanding terminal infrastructure, improving digital customs coordination, and diversifying its logistics service base beyond transit functions.

5.1.4. Belarus

In the railway dimension, Belarus’s results were considerably weaker. The railway development score (32.2) and terminal capacity (3.7) highlight infrastructure deterioration and inadequate wagon availability. Although customs procedures performed relatively better (70.7), due to ongoing digitalization initiatives and bilateral agreements, the border connectivity score (19.0) indicates severe bottlenecks, especially at the Brest–Małaszewicze crossing.

Belarus recorded the lowest overall readiness score (36.5), reflecting deficiencies in the railway dimension. In the LPI, the country scored 43.6 (ranked 80th globally), with its strongest indicator being timeliness of shipments (52.5), followed by infrastructure quality (42.5), and logistics services quality. However, Belarus still faces limitations in tracking systems and shipment coordination. Belarus’s overall performance aligns with the “deficient” category of the readiness scale, signaling the need for substantial modernization in both physical and institutional logistics systems. Without accelerated investment in terminal infrastructure and railway development, the country risks becoming a bottleneck for NELBEC freight flows between Russia and the EU.

Therefore, the results indicate that Russia’s leadership stems from its railway strength, while Poland’s advantage arises from its logistics efficiency. Kazakhstan and Belarus, though strategically located, still face significant operational and infrastructural gaps. This asymmetry highlights the need for targeted investment in digitalization, intermodal terminal capacity, and border-crossing efficiency to enhance the overall functionality of the NELBEC.

5.2. Comparison with Previous Studies

The findings of this study both confirm and extend insights from earlier research on the Belt and Road Initiative (BRI), particularly regarding the strategic role of rail transport in Eurasian connectivity. Previous studies, such as Uygun and Ahsan [1] and Pendrakowska [47], have emphasized the growing importance of railway corridors for linking China and Europe, citing their advantages in cost efficiency, speed, and environmental impact compared to maritime transport. The results of this research corroborate these perspectives, where countries with higher railway readiness, like Russia and Poland, also exhibit stronger overall preparedness for integration into the NELBEC.

Our results further align with the findings of Zhang et al. [19] and Nitsche [6], who identified border-crossing nodes as persistent bottlenecks in Eurasian logistics. The low readiness score of Belarus, driven by congestion and infrastructural limitations at Brest–Małaszewicze, provides empirical evidence supporting their conclusions. However, this study advances the discussion by incorporating railway-specific indicators such as terminal capacity, customs digitalization, and FDI inflows in rail infrastructure, dimensions that have been largely neglected in earlier studies relying solely on the World Bank’s LPI [15,23].

Beyond confirming previous findings, the proposed methodology fills a significant gap in the literature. Most existing assessments focus narrowly on trade facilitation or logistics performance, whereas this research integrates both institutional and physical infrastructure dimensions. This dual focus provides a more comprehensive measure of corridor readiness and highlights interdependencies between logistics management and railway infrastructure, which is an approach consistent with recent methodological recommendations by Yu et al. [20], and highlights the importance of selecting relevant and understandable indicators, especially in planning and infrastructure contexts [41].

Methodologically, this study contributes a novel composite index framework that combines standardized indicators, expert-derived weighting via the BPA approach, and additive aggregation. Such integration offers a replicable and adaptable structure for measuring readiness across transnational infrastructure projects. The use of proxy indicators, as suggested by Haou et al. [48], was particularly valuable in addressing data limitations in NELBEC countries, where official statistics on railway performance, terminal capacity, and digitalization remain fragmented. This approach ensures that essential aspects of logistics and railway readiness are represented, even when direct measures are unavailable. In comparison with traditional indices such as the LPI, the RLRI provides a finer-grained understanding of corridor dynamics by distinguishing between logistical management efficiency and physical transport capability. Thus, it bridges a long-standing methodological gap in the quantitative assessment of the BRI’s overland corridors.

6. Conclusions

This study developed a Railway Logistics Readiness Index to assess the preparedness of four key NELBEC countries, which are Poland, Russia, Kazakhstan, and Belarus, for integration into the BRI. By combining the World Bank’s LPI with newly proposed railway-specific indicators, the research provides a multidimensional view of logistical and infrastructural readiness. The results reveal marked disparities in performance with only Poland and Russia reaching moderate readiness levels. Russia emerged as the top performer, driven by its vast rail capacity but hindered by administrative inefficiencies; Poland followed, supported by EU-standard infrastructure and customs digitalization. Kazakhstan showed moderate readiness, benefiting from strategic positioning yet constrained by weak terminal capacity, infrastructure and cross-border nodes. Belarus ranked last, limited by outdated infrastructure and bottlenecks.

Methodologically, the study advances corridor assessment by integrating logistics and railway dimensions within a single composite index. The approach combines normalization, expert-based weighting, and additive aggregation to extend beyond conventional LPI analyses, offering a more context-specific framework that captures both structural capacity and operational efficiency. This provides a replicable tool for evaluating other BRI corridors or multimodal transport systems.

6.1. Practical and Policy Implications

The empirical results offer actionable insights for policymakers and international stakeholders. Russia’s performance illustrates how strong railway infrastructure can compensate for weaker logistics efficiency. Targeted improvements in customs procedures, digital systems, and intermodal infrastructure could further enhance Russia’s role as a central transit hub. Poland’s high readiness underscores the benefits of EU-funded infrastructure projects, customs harmonization, and technological modernization. The country can strengthen its position as the main European gateway of NELBEC by addressing rail congestion at Małaszewicze and expanding wagon capacity.

Kazakhstan, despite its strategic location and investments at Khorgos, still faces limitations in terminal capacity and customs transparency. Expanding handling capacity and accelerating digital integration are crucial for maintaining competitiveness. Belarus remains the most vulnerable node in the corridor, requiring urgent modernization of its logistics infrastructure and the elimination of administrative bottlenecks to prevent systemic delays.

Political factors play a decisive role in shaping the effective implementation of corridor strategies, beyond technical and logistical aspects. The success of NELBEC hinges on sustained cross-border cooperation, regional stability, and policy alignment among participating states. Ongoing geopolitical tensions and sanctions regimes affect railway flows between Russia, Belarus, and the European Union, influencing investment attractiveness and operational continuity. Institutional coordination through multilateral mechanisms, such as the EEU and the EU, can strengthen the corridor’s governance framework and ensure the practical application of the readiness index. These findings have clear policy implications regarding coordinated cross-border investments, digital harmonization, and diplomatic engagement aimed at improving corridor performance. Improved railway connectivity reduces transit costs and times, and strengthens regional economic integration, which is one of the BRI’s core objectives.

6.2. Limitations and Future Research

Despite its contributions, the study faces several limitations inherent to its data and methodological scope. First, the availability and consistency of national-level data remain uneven. Several indicators such as terminal handling capacity and customs digitalization required the use of proxy variables, which, while informative, may not fully capture the complexity of real-world logistics systems. Second, the weighting process based on expert judgment introduces an element of subjectivity, and results could vary whether different experts or weighting techniques (e.g., AHP, PCA or entropy methods) were employed.

Moreover, the analysis focuses exclusively on four NELBEC countries. Expanding the model to include additional BRI participants (e.g., China, Germany) could enhance comparative robustness and reveal broader regional patterns. Future research could integrate dynamic indicators such as investment flows over time, operational reliability metrics, and environmental performance, to assess how corridor readiness evolves. Moreover, linking this composite index with trade volume data could help quantify how improvements in logistics and railway systems translate into tangible economic gains.