Maritime industry’s digital push accelerates amid cyber risks and data gaps

The study identifies multiple enablers of digitalization across three dimensions - technological, organizational, and environmental. Technologically, advances in artificial intelligence, blockchain, Internet of Things (IoT), and digital twins are driving operational efficiency, visibility, data integration, and risk reduction. Automation and AI are increasingly being used for predictive maintenance, real-time route optimization, and supply chain decision-making. Digital ecosystems also enable real-time information sharing, which helps synchronize operations between ports, shipping lines, and freight forwarders.

As maritime logistics faces growing demands for efficiency, transparency, and sustainability, digital transformation has emerged as both a necessity and a challenge. A new study published in the Journal of Marine Science and Engineering, titled “Digitalization in the Maritime Logistics Industry: A Systematic Literature Review of Enablers and Barriers”, maps the current landscape of this transformation. The study offers a comprehensive analysis of 117 academic publications to identify 19 enablers and 10 barriers shaping digital adoption across global maritime logistics.

Led by researchers Fangli Zeng, Anqi Chen, Shuojiang Xu, Hing Kai Chan, and Yusong Li, the review systematically categorizes factors using the Technology–Organization–Environment (TOE) framework, coupled with innovation diffusion theories. Their work provides a conceptual foundation for advancing digital strategies in an industry deeply reliant on tradition, manual processes, and fragmented infrastructure, and where technological gains remain unevenly distributed.

What enables digitalization in maritime logistics, and which technologies are driving transformation?

The study identifies multiple enablers of digitalization across three dimensions - technological, organizational, and environmental. Technologically, advances in artificial intelligence, blockchain, Internet of Things (IoT), and digital twins are driving operational efficiency, visibility, data integration, and risk reduction. Automation and AI are increasingly being used for predictive maintenance, real-time route optimization, and supply chain decision-making. Digital ecosystems also enable real-time information sharing, which helps synchronize operations between ports, shipping lines, and freight forwarders.

Security enhancements through digital solutions such as blockchain-based container tracking and digitalized seafarer identification improve both physical and cyber protection. Moreover, the integration of smart platforms allows for real-time monitoring of cargo, automated customs procedures, and dynamic port operations, all of which contribute to cost savings and competitive advantage.

Organizationally, digitalization is fueled by management awareness, the demand for cost reduction, and the presence of skilled technical personnel. Operational streamlining is a recurring benefit, as is the growing use of data analytics to support decision-making in areas like ETA forecasting and resource allocation. Investment remains a key enabler, particularly in building infrastructure like port automation systems, smart container technology, and digital twin simulation environments.

On the environmental front, sustainability goals, global trade development, and pressure from customers and competitors are driving digital adoption. The COVID-19 pandemic was also cited as a significant accelerator, compelling stakeholders to adopt digital solutions in response to crisis-induced disruptions. Regulatory environments, when supportive, provide legal and policy frameworks to foster innovation and inter-organizational collaboration.

What are the main obstacles slowing digital transformation in the sector?

Despite growing interest and technological maturity, the study identifies ten barriers that continue to impede the digitalization process. Chief among them is cybersecurity risk. As digitalization expands, so does the attack surface. Data leaks, ransomware, and privacy breaches are cited as critical concerns. Many maritime organizations hesitate to share sensitive data across platforms, fearing loss of competitive advantage or exposure to legal liabilities.

Another major challenge is data acquisition and integration. Maritime logistics stakeholders often operate isolated systems that produce incompatible datasets. Information silos, poor data quality, and a lack of standardized protocols hinder seamless communication and decision-making. This fragmentation impedes the development of centralized or distributed digital platforms.

Organizational barriers include limited workforce digital literacy, resistance to change, and persistent reliance on physical documents. The industry's culture, deeply rooted in traditional practices, has made some operators reluctant to replace legacy systems with digital alternatives. Infrastructure deficits are also pronounced, especially in ports across developing economies, where investment in smart infrastructure remains insufficient.

Environmental constraints include outdated regulatory frameworks and high implementation costs. The lack of harmonized global standards for digital systems, particularly in autonomous shipping and smart port development, slows innovation. Complexity in managing stakeholder relationships, data volumes, and operational variability also adds to the friction. Finally, geographical and operational imbalances mean that even within a single country or supply chain, digital capabilities may differ significantly among stakeholders, further complicating integration.

How should the maritime logistics sector proceed to overcome these challenges and scale digitalization sustainably?

To address the fragmented and uneven progression of digital adoption, the authors propose an integrated conceptual framework combining the TOE model with the Diffusion of Innovation (DOI) theory. The framework aligns stakeholders, ports, governments, shippers, carriers, and financial institutions, across six core dimensions of innovation: relative advantage, compatibility, complexity, trialability, observability, and environmental readiness.

This framework suggests that tailored strategies are required for different actors depending on their role, size, and digital maturity. For instance, large ports might invest in AI-based automation and predictive analytics, while smaller ports may prioritize basic infrastructure upgrades and workforce training. Emphasis is also placed on non-managerial stakeholders. Operational staff such as terminal workers, ship crews, and customer service personnel must be included in training programs to foster a digital-first culture and reduce resistance.

Future research, the authors argue, should move beyond general case studies and focus on empirical validation of the proposed framework in real-world settings. Particular attention should be paid to workforce development, the role of intermediary technology providers, and the co-evolution of regulations with emerging technologies like blockchain and AI. Long-term assessments of the environmental impacts of digital adoption such as decarbonization and energy efficiency also represent a key research frontier.