The Belt and Road Initiative (BRI), launched in 2013, aims to improve economic connectivity across Asia, Europe, Africa, and parts of South America. A crucial component is the 21st Century Maritime Silk Road (MSR), focused on developing maritime routes and port facilities. The MSR's success hinges on sustainable logistics practices, encompassing eco-friendly transportation and efficient resource management. Existing research often focuses on economic growth and trade, neglecting a holistic evaluation of sustainability. This study addresses this gap by assessing the sustainable logistics potential of key countries along the MSR. It integrates Data Envelopment Analysis (DEA), a quantitative method for assessing the efficiency of decision-making units (DMUs), with Prospect Theory, a behavioral economics model that accounts for risk aversion and loss aversion in decision-making. This combined approach allows for a more nuanced understanding of the sustainable logistics capabilities of these countries, considering both objective performance metrics and the behavioral aspects of decision-makers. The study aims to provide insights into how these countries can improve their logistics capabilities to align with sustainability principles and efficient resource management along the MSR, contributing to the broader goals of the BRI and global sustainable development.

Existing literature on the BRI extensively examines its economic and strategic aspects, including the geo-economic ties between China and MSR countries. Studies using social network analysis highlight China's expanding influence and the emergence of strategic nodes. Research also focuses on the sustainability of Chinese ports within the BRI framework, evaluating their capabilities for sustainable development and prioritizing port investments in Southeast Asia using link prediction theory. Another stream of research examines the impact of Chinese maritime investment on coastal livelihoods, highlighting complexities and opportunities related to the blue economy. Concerning MSR logistics specifically, studies investigate the impact of port infrastructure connectivity on logistics performance and economic growth, the assessment of supply chain risks using fuzzy logic, and the operational efficiency of MSR ports using DEA. Further studies explore the spatio-temporal transformations in container ports along the MSR and the evolving port network from a sustainable development perspective. Despite these advancements, a comprehensive evaluation of sustainable logistics potential across economic, environmental, infrastructure, governance, and innovation factors remains a significant gap in the literature. This study fills this gap by providing a holistic assessment of sustainable logistics readiness.

This research employs a novel methodology that integrates Data Envelopment Analysis (DEA) with Prospect Theory. DEA is a well-established technique in operations research used to assess the relative efficiency of DMUs based on their input-output relationships. The study uses both CCR and BCC models to account for constant and variable returns to scale. Prospect Theory, a behavioral economics model, is incorporated to account for the risk-averse and loss-averse nature of decision-making. The model is structured in three key steps: 1. **Normalization of Inputs and Outputs:** Inputs (e.g., investment, construction) and outputs (e.g., economic indicators, environmental indicators, infrastructure metrics) are normalized to allow for a fair comparison across countries. 2. **Identification of Reference Points:** Positive and negative reference points are determined for each input and output, reflecting the reference dependence principle of Prospect Theory. 3. **Construction of the Risk-Considering DEA Model:** A DEA model is constructed incorporating normalized values, reference points, and the parameters γ and δ from Prospect Theory, which reflect the decision-makers' gain-risk and loss-risk attitudes. The model also includes a parameter φ that represents the relative weighting of gains versus losses. This model is then used to evaluate the efficiency of the selected countries along the MSR based on their performance across the chosen indicators. The research selects 9 key countries along the MSR as DMUs. Data for inputs and outputs are collected from various international organizations, including the IMF, IEA, UNCTAD, WGI, World Bank, WIPO, UNIDO, and WTO. The inputs selected are China's cumulative investment and construction in each of the target countries, while the outputs are grouped into five categories: economic, energy and environmental, infrastructure and logistics, governance and stability, and innovation, comprising twenty-nine indicators in total. The model is applied separately to each of the five groups of outputs to assess the efficiency across each factor.

The study assesses the sustainable logistics performance of nine key countries (Djibouti, Greece, India, Indonesia, Italy, Kenya, Malaysia, Sri Lanka, and Vietnam) along the MSR. The key findings are presented as separate efficiency scores for each of the five factors (economic, energy and environmental, infrastructure and logistics, governance and stability, and innovation) for each country. China's investment and construction in each country are used as inputs in the DEA model. Economic factors considered include commercial service exports and imports, export and import value indexes, GDP, inflation, merchandise trade, and net trade in goods. Energy and environmental factors consider energy intensity, adjusted savings for carbon dioxide damage, and CO2 emissions. Infrastructure and logistics factors include container port traffic, costs to export and import, logistics performance index, machinery and transport equipment in manufacturing, and time required for various trade-related activities. Governance and stability factors considered are control of corruption, government effectiveness, political stability, and rule of law. Innovation factors include human capital index, industrial design applications, and patent applications. The results indicate a diverse performance across countries and factors. Vietnam exhibits high cost efficiency in the economic factor. Indonesia shows strong performance in sustainability and governance. Malaysia demonstrates a balance across multiple factors. India, Greece, Djibouti, and Kenya display strengths in various aspects. The risk-considering DEA model results quantify the performance of each country across the five factors, with some countries demonstrating higher efficiencies in specific areas. Detailed data tables in the original paper provides a full picture of the decision matrix and normalized decision matrix that was used for analysis.

The findings reveal a complex interplay of factors influencing sustainable logistics performance along the MSR. The integrated DEA-Prospect Theory model provides a more comprehensive and nuanced assessment than traditional approaches, capturing both objective performance and behavioral dimensions of decision-making. The results highlight the importance of a holistic approach to sustainable logistics development, emphasizing the interconnectedness of economic, environmental, infrastructural, governance, and innovation aspects. The diverse performance across countries underscores the need for tailored strategies focused on specific strengths and weaknesses. The study’s findings offer valuable insights for policymakers to inform investment decisions, infrastructure development, and policy interventions aimed at fostering sustainable trade along the MSR. The inclusion of behavioral factors enhances the model’s practical relevance, providing insights into decision-making processes that influence logistics performance. The study contributes to both the academic understanding of sustainable logistics and the practical application of advanced analytical tools for policymaking and business strategy.

This study offers a novel approach to evaluating sustainable logistics potential along the MSR using a DEA model enhanced by Prospect Theory. The key finding is a comprehensive ranking of nine key countries' efficiency across economic, environmental, infrastructural, governance, and innovation factors. The research highlights the diverse strengths of these countries and identifies areas for improvement. The integrated DEA-Prospect Theory model provides a more robust and nuanced assessment than traditional methods. Future research could focus on incorporating direct behavioral data, further exploring cultural and political factors, and expanding the scope of the study to include a broader range of countries along the MSR.

The study acknowledges limitations related to the indirect measurement of decision-makers' psychological behavioral coefficients within the DEA-Prospect Theory model. The reliance on subjective judgments and behavioral preferences may affect the accuracy of the assessment. Furthermore, the analysis primarily focuses on efficiency metrics without exploring other significant factors, such as cultural, political, or legal factors, that influence logistics capabilities. These limitations highlight areas for future research to further enhance the model's robustness and provide more complete insights into sustainable logistics along the MSR.