TAEO - Technology integration in maritime and ports operations

The shipping industry is a significant contributor to global greenhouse gas emissions, and there's growing pressure for it to adopt more sustainable practices. This research explores how digital technologies, particularly AI, can drive green innovation in the sector. Using Structural Equation Modelling (SEM), we examine how data-driven capabilities-such as digital collection, analysis, and application-can contribute to sustainable technological advancements. One of the key findings is the critical role AI awareness plays in fostering collaboration between employees and AI systems, leading to the development of green technologies. When employees have a deeper understanding of AI, they can work more effectively with these systems, improving decision-making, optimizing processes, and generating sustainable solutions. This paper offers practical advice for shipping companies, emphasizing the importance of fostering AI awareness at all levels of the workforce and positioning AI as a tool for innovation. Additionally, it suggests policy actions for governments to support AI adoption in sustainability efforts, such as offering incentives and encouraging knowledge-sharing. Ultimately, this study contributes to the growing body of research on digital transformation, AI, and sustainability, laying the groundwork for future exploration of how AI can drive green innovation in various industries.

The efficiency, resilience, and overall quality of services provided by international supply chains focused on sea-land logistics increasingly depend on the ability to implement IT-based, data-driven, intangible infrastructures and innovative software applications. In this perspective, several emerging digital technologies enable the development of IT-based Decision Support Systems (DSS) which paves on real-time, data-driven innovative tools. These solutions enable the availability of relevant data and information at the right time, right "place", and in the appropriate manner.
Notably, the competitiveness of modern gateway ports increasingly depends on key success factors, which are external respect to the port domain, and that constitute a strategic leverage for serving wider hinterland areas. Hence, the success of international sea-land logistics, ports, and related economic actors is expected to increasingly rely on innovative IT-based solutions for supporting the decision-making process of the different stakeholders across supply chains and urban areas (e.g., service providers, regulators, citizens, local companies and motorway users).
The study, in particular, scrutinizes the importance of efficient and resilient highway infrastructures capable of avoiding queuing and bottlenecks in servicing major gateway ports. Next to this, it investigates emerging digital technologies, which can enable the development of integrated data-driven dashboards for supporting the decision-making process of both public and private actors, including B2B and B2C users. 
This study offers policy and managerial implications about the benefits of implementing IT-based DSS conceived to manage highway capacity efficiently, also bringing insights to support Port Authorities and regulators, as well as for inspiring users in their travel choices and mobility behaviors.

Maritime companies are actively advancing digital integration and adopting various strategies to support this transformative transition. Port State Control (PSC) plays a significant role in safety at sea and protection of the environment through inspection of foreign ships. This paper explores the correlation between digitalization and PSC deficiencies and detentions basis on a case study. This research utilizes in the most effective way real-case data collected from the fleet of a reputable maritime company. The aim is to identify and analyze the various characteristics linked to the digital transformation within the organization before and after the implementation of digital systems of monitoring. The results emphasize that the adoption and implementation of digital technologies by maritime companies, such as telemetry, have the potential to substantially reduce the likelihood of port state control deficiencies being imposed.

The complexity of technology adoption (TA) dynamics becomes evident in large-scale innovation ecosystems, such as the maritime one. Despite its relevance, research to date has explained TA mainly through individual-centred models that neglect the relational dynamics that influence adoption decisions in multi-actor ecosystems. To remain competitive, maritime supply chain actors should start fostering a culture in which TA is a strategic lever for growth, while recognising the role of relational dynamics in shaping TA decisions. To fill this gap, this research explores the relational determinants that adopters, or technology buyers, perceive as critical in their TA decisions and quantifies their relative importance in decision-making situations. To achieve this, a rigorous mixed-method approach is adopted. First, a qualitative phase, based on semi-structured interviews, enables the collection of authentic insights into TA decision-making processes. These findings inform the quantitative phase, which applies Discrete Choice Analysis (DCA) to understand how buyers make adoption decisions between competing alternatives. Preliminary results show that buyer decision-making autonomy and buyer-seller trust are the decisive determinants of TA in the maritime sector. The first strengthens adoption decisions, while the second represents a necessary prerequisite in TA decision-making processes.

The advent of digital technologies offers an opportunity for logistics service providers (LSPs) to transform their business models. However, this often introduces competition among LSPs who used to cooperate to meet end customer needs, resulting in increasingly complex market relationships. To fully assess the overall impact of digitalization on logistics chain efficiency, it is essential to investigate whether such complex relationships could negatively influence the efficiency of entire chain. This study employs Transaction Cost Economics (TCE) theory to conceptualize the effects of LSP relationships on transaction costs. By temporarily setting aside the cooperation mechanism, we focus on the competition mechanism among LSPs and analyze how it affects some transaction factors incl. uncertainty and opportunism, which ultimately drive up transaction costs. Hypotheses will be tested through empirical cases collected through interviews. The findings hopefully can contribute to a deeper understanding of maritime logistics market performance in the digital age, offering valuable implications for both theory and practice.