## 1 Introduction  
The concept of smart ports was introduced as a solution to various port challenges, including achieving operational excellence, relocating activities, and meeting new business requirements. Smart ports utilize modern technology to transform traditional port services into interactive and dynamic systems, aiming to enhance efficiency and transparency. Key features of smart ports include supply chain integration and the automation of port operations and equipment. These features of integration and automation help improve the port's overall competitiveness [1]. Smart ports use data analytics and Internet of Things (IoT) technology to enable real-time decision-making and predictive maintenance of infrastructure. These innovations assist in reducing operational risks and downtime [2]. The use of green and sustainable technologies, such as renewable energy systems and pollution monitoring, guarantees that smart ports meet worldwide environmental requirements, rendering them resilient and socially responsible [3]. Additionally, smart ports save time and money in terms of document management and human resources, while also improving monitoring, traffic management, congestion reduction, and productivity. This results in added value and customer satisfaction [4]. Recent research has highlighted the role of digital transformation in maritime logistics, especially in relation to sustainability and artificial intelligence-driven decision-making [5]. Furthermore, deep learning approaches have been explored as a means of improving maritime surveillance and operational efficiency [6]. These advancements align with the growing focus on smart port technology and underscore the need for advanced decision-making frameworks like NCMs to manage the intricate interconnections within port operations. For port authorities and industry stakeholders, assessing smart port performance is crucial for making strategic decisions about infrastructure expenditure, regulatory regulations, and operational changes. A thorough performance review enables stakeholders to uncover inefficiencies, optimize resource allocation, and improve service quality, ensuring competitiveness in the increasingly digitalized and automated marine industry. Performance indicators not only assist in comparing against global standards but also in ensuring regulatory compliance, sustainability goals, and economic efficiency. Despite the advances made, current research on smart port performance evaluation has several shortcomings. One fundamental limitation is the absence of a systematic and scientifically rigorous methodology for accurately assessing a port's level of intelligence while considering dynamic interdependence and uncertainty [7]. Traditional evaluation models often rely on predetermined criteria and struggle to incorporate changing data sources and real-time updates [8]. Additionally, they do not simultaneously consider degrees of truth, falsehood, and indeterminacy, which are essential for modeling complex and dynamic scenarios. Conducting an effective performance evaluation is very helpful for realizing the potential of smart ports. Performance measurement provides a systematic approach for determining how well a smart port achieves its operational, economic, and environmental objectives. The growing interest in performance measurement has resulted in the development of various frameworks that organizations use to identify the metrics they should use to evaluate their performance [9; 10; 11]. Researchers have conducted extensive studies to optimize ports and establish a model for smart ports. These studies involve optimizing logistics and supply chains, enhancing port services, reducing environmental impact, and minimizing equipment usage [12; 13; 14; 15; 16]. However, researchers in a study by [17] suggest that the decision-making process is complex and challenging to quantitatively model, due to limited numerical data, the unstructured nature of the problem, and reliance on verbal communication.