Guest editorial: Emerging insights from synchromodality and co-modality research

Over the past decade, the global transport and logistics sector has undergone a rapid transformation driven by technological innovation, environmental imperatives and the pursuit of operational resilience. Advances in digital platforms, real-time data integration and algorithmic decision support have significantly enhanced the ability to coordinate flows across modes, enabling more flexible and demand-responsive operations (Kong et al., 2025). Within this evolving landscape, synchromodality and co-modality have emerged as two complementary paradigms redefining how multiple transport modes are jointly planned and utilised, supported by new digital infrastructures that allow dynamic switching and seamless multimodal orchestration.Synchromodality refers to the dynamic and real-time management of freight flows across interconnected modes – such as rail, road, barge and air – where shippers can switch between modes in response to operational or environmental conditions (Verweij, 2011). It represents an evolution beyond intermodal and co-modal transport, emphasising synchronisation, digital integration and decision flexibility (Haller et al., 2015; Tavasszy et al., 2017). In contrast, co-modality highlights the joint use of passenger and freight transport infrastructure, advocating for the optimal combination of services within a unified system to enhance both efficiency and sustainability (Zhu et al., 2023). While synchromodality prioritises real-time mode substitution and system-wide coordination, co-modality focuses on shared capacity and the cross-utilisation of transport assets for people and goods. Together, they offer a systemic response to contemporary challenges – congestion, emissions, the energy transition and urban accessibility – by promoting seamless, intelligent and resource-efficient mobility networks.This Special Issue of Exploring Synchromodality and Co-modality: Pathways to Sustainable and Efficient Transportation System, brings together interdisciplinary perspectives and emerging evidence on how digitalisation, optimisation, behavioural insight and governance mechanisms can advance integrated mobility. The collected studies highlight innovative modelling approaches, empirical validations and real-world applications that jointly illustrate how these paradigms can accelerate the transition toward sustainable, adaptive and data-driven transport systems. Beyond the operational layer, the contributions also underscore the socio-technical and institutional changes needed to foster logistics ecosystems capable of real-time responsiveness and cross-modal collaboration.From an academic standpoint, synchromodality has evolved from a classical multimodal concept into a supply-chain-centric framework where flexibility, cooperation and synchronisation form its core principles (Nobis, 2007; Rondinelli and Berry, 2000). Dong et al. (2018) reframed it as “Synchromodality from a Supply Chain Perspective,” arguing that a holistic view of logistics processes amplifies mode-shift potential without sacrificing cost or service levels. Pfoser et al. (2016) identified cooperation and transparency as decisive success factors, while Giusti et al. (2019) emphasised the pivotal role of orchestration platforms in enabling real-time decision-making. More recently, the emergence of digital logistics platforms has further strengthened this paradigm by facilitating decentralised yet coordinated decision-making, allowing multiple actors to align procurement, transport planning and service contracting through market-based or algorithmic mechanisms (Kong et al., 2023). Haller et al. (2015) and Sakti et al. (2023) likewise associated synchromodality with the vision of the Physical Internet, highlighting synchronisation as a foundation for adaptive, platform-driven and learning-based logistics.In parallel, co-modality research has followed a progressive trajectory – from conceptual framing to technological enablement, operational optimisation and stakeholder coordination. Early work by Trentini and Mahléné (2010) introduced the concept of passenger–goods cohabitation as a pathway to reduce economic and environmental externalities. Building on this foundation, Ronald et al. (2016) showed how ICT and on-demand mobility technologies make such integration practically feasible. More recent studies by Yang et al. (2023, 2024) developed crowdsourced and schedule-based co-modality models, demonstrating that synchronised passenger–freight systems can achieve cost-effective, low-emission urban distribution. Finally, Ma et al. (2023) examined cooperative and competitive interactions among operators through game-theoretical analysis, revealing how coordinated arrangements can yield Pareto-improving outcomes. Collectively, these studies trace a clear evolution from conceptual vision to intelligent and collaborative implementation, highlighting synchronisation, cooperation and digital intelligence as the core enablers of sustainable co-modality.Across the globe, synchromodality has found fertile ground in major logistics corridors and ports. In Europe, the Port of Rotterdam epitomises digitally orchestrated logistics through its Port Vision 2030 and integrated platforms such as Pronto, Navigate and Portmaster, which align maritime, barge, rail and truck operations (portofrotterdam.com). Similar ambitions are visible in the Horizon 2020 SYNCHRO-NET project (synchronet.eu), which merged cloud optimisation and smart-steaming technologies to improve both energy efficiency and network robustness. In the USA, the Georgia Ports Authority's Savannah model extends this philosophy inland: its Mason Mega Rail complex and associated hubs synchronise maritime and rail flows (gaports.com), while the Port of Los Angeles' “Port Optimizer™” platform links terminals, carriers, and shippers in a single digital environment, enabling proactive modal decisions (portoflosangeles.org). In China, the Western Land–Sea New Corridor and the Ningbo–Zhoushan Port network illustrates national-scale integration of rail, sea and road under unified scheduling and data systems (zjseaport.com). Despite differing institutional contexts, all these efforts converge on a shared vision – turning multimodality into synchromodality through real-time coordination, digital governance and dynamic routing based on time, cost, reliability and carbon performance.Meanwhile, co-modality has matured as an experimental yet increasingly viable approach to urban and regional logistics integration. European cities such as Dresden and Zürich have shown that passenger transport infrastructure can be repurposed for freight movement without compromising service quality (e.g. CarGoTram). In the USA, co-modality pilots like Seattle's Freight and Transit Lane and New York's Consolidated Transportation System explore how transit corridors and fleets can accommodate parcel flows (urbanfreightlab.com). Although challenges remain in governance and scheduling, these trials highlight the efficiency gains achievable through shared use of infrastructure. In China, projects such as Shenzhen's “Rail Transit Logistics”, integrating metro, drones and autonomous vehicles for hub-to-station same-day delivery and the passenger–freight–post integration program in rural areas extend the co-modality principle to both high-density and underserved regions. By blending physical networks with digital coordination platforms, these initiatives showcase how passenger–freight integration can enhance accessibility, reduce costs, and support inclusive, low-carbon logistics development.As reflected in both academic inquiry and industrial practice, synchromodality and co-modality are evolving from niche concepts into recognised foundations of integrated transport innovation. Their feasibility has been validated through corridor programs, port ecosystems and city-scale pilots worldwide. While large-scale adoption remains an ongoing challenge, these early experiences have revealed the tangible potential of synchronised and shared mobility to enhance the efficiency, sustainability and resilience of modern logistics systems.The purpose of this Special Issue, therefore, is not to provide definitive solutions but to offer a timely forum for scholars and practitioners to present the latest insights, methodologies and applications related to these emerging paradigms. By consolidating cross-disciplinary research and empirical findings, this issue aims to deepen understanding, identify practical barriers to implementation, and stimulate continued innovation toward scalable and adaptive multimodal transport systems capable of handling the increasing complexity and dynamism of modern logistics networks. As shown in Figure 1, to position the twelve accepted papers within the broader challenges of modern logistics research, this Special Issue classifies them according to the core pain points they address rather than by methodology or application domain. Five recurring pain points emerge across the contributions: misaligned incentives among decision makers, time-critical decisions under uncertainty, inefficient layout of logistics nodes and flows, high-cost energy supply and infrastructure constraints and low adoption of data platforms and governance mechanisms. This pain-point-driven perspective highlights not only the diversity of problem contexts – ranging from synchromodal freight systems to urban mobility and energy-logistics integration – but also the shared structural challenges that motivate current advances in modeling, analytics and decision-support design.The Special Issue received 23 manuscript submissions from scholars and practitioners around the world. After several rounds of rigorous peer review, 12 papers were accepted for publication, resulting in an overall acceptance rate of 52% and a rejection rate of 48%. The accepted papers collectively address a broad range of challenges related to the implementation and advancement of synchromodality and co-modality. The solutions and issues investigated by these contributions are summarised in Table 1. These studies can be organised into three interrelated research frontiers: (1) Sustainable energy-logistics integration and resilient network design; (2) Urban and operational coordination in multimodal contexts; (3) Institutional, behavioural and governance mechanisms for synchromodal adoption. Each group reflects a distinct layer of system integration – from infrastructure and technology to decision processes and stakeholder behaviour.Several contributions investigate how multimodal transport and renewable energy integration jointly support carbon neutrality and supply-chain resilience.Lei et al. (2026) propose a stochastic optimisation framework for designing resilient carbon capture, utilisation and storage networks under disruption risk. Their model integrates proactive facility fortification with reactive transshipment among pipelines, trucks and ships, illustrating how multimodal adaptability can minimise both cost and emission volatility. Similarly, Li et al. (2026) develop a mixed-integer nonlinear optimisation approach for hydrogen logistics systems powered by hybrid electricity sources. Their findings reveal that coupling renewable generation with flexible transport modes enhances economic and environmental performance simultaneously.Beyond energy systems, Zhang et al. (2026a) address the tactical and operational planning of multimodal dry-port networks. Their two-stage stochastic model captures disruptions in rail, road, and maritime links, demonstrating how dry ports can act as synchro-modal hubs – reallocating flows dynamically and balancing inventory, production and routing decisions. Collectively, these studies signal a paradigm shift: resilience is no longer achieved through redundancy, but through designed optionality – co-optimising energy sources, logistics modes and temporal buffers within one analytical framework.Urban logistics and transport hubs serve as vital arenas for applying synchromodal principles at the operational level. Within dense, time-sensitive and resource-constrained environments such as airports, high-speed-rail terminals and urban delivery networks, coordination across vehicles, infrastructure and schedules becomes indispensable. Yu et al. (2026a) address this challenge through an integrated optimisation of gate reassignment and taxiway routing at Hong Kong International Airport. Their time–space network model eliminates spatial conflicts and achieves real-time synchronisation of aircraft movements, illustrating how synchromodality can enhance throughput and fuel efficiency in complex terminals.Tan and Kang (2026) address this challenge through a comprehensive model that integrates electric-vehicle routing with parking and charging decisions. Their findings show that parking availability and charging density jointly shape the economics and carbon profile of last-mile freight, underscoring the need for integrated spatial and energy management. Zhang et al. (2026b) explore forward-and-reverse coordination in e-commerce logistics by developing an optimisation model for simultaneous pickup and delivery. Their hybrid simulated-annealing and tabu-search algorithms achieve near-optimal solutions, demonstrating how synchronised vehicle use can reduce emissions and improve service reliability.Xu et al. (2026) examine time-critical food logistics within China's high-speed-rail network. Their stochastic scheduling framework balances earliness and tardiness costs, synchronising meal preparation and delivery with fixed train timetables – an operational embodiment of synchromodal coordination under uncertainty. Luo et al. (2026) investigate large-scale pharmaceutical distribution and propose a clustering-based algorithm that combines continuous facility location with heuristic routing evaluation. Their approach integrates strategic and operational decisions, providing a data-driven tool for re-designing urban logistics networks.Extending this discussion to a safety-critical domain, Xue and Liu (2026) examine medical-waste transportation under carbon-neutral objectives. Using simulation and entropy-based evaluation, they compare fossil-fuel, electric and hybrid vehicle fleets. Their results indicate that full electrification achieves the best environmental performance, while hybrid configurations offer practical transitional solutions.Across these studies, a shared insight emerges: synchromodality in urban logistics does not require multiple transport modes but rather the synchronisation of time, space, and energy resources. By harmonising operational constraints and leveraging digital intelligence, urban transport systems can achieve both efficiency and sustainability.Technological and operational advances will remain limited unless supported by coherent governance and behavioural acceptance. Several contributions in this special issue investigate how institutional frameworks and human factors shape the transition towards synchromodal transport.Wu et al. (2026) construct a game-theoretic model for electric-vehicle battery recycling under asymmetric information and government intervention. Their dual-contract mechanism addresses both adverse selection and moral hazard, revealing how subsidy policies can align private incentives with public sustainability goals. Kumar et al. (2026) identify the key enablers of synchromodal logistics through neutrosophic interpretive structural modelling and MICMAC analysis. Their results emphasise electronic data exchange and legal–political frameworks as foundational drivers that enable infrastructural development, partnership formation, and carbon-regulation effectiveness. Complementing these systemic insights, Yu et al. (2026b) adopt a behavioural perspective to examine the user acceptance of mobility-as-a-service platforms in Shenzhen. Their structural equation modelling results show that comfort, effort and performance expectancy strongly influence adoption intentions, suggesting that technological integration must be matched with user-centred design and communication.Taken together, these studies reinforce that synchromodality is not solely a technical innovation but a socio-technical transition. Achieving large-scale adoption requires regulatory clarity, digital interoperability and behavioural trust – each functioning as a synchronised layer of the same integrated system.In summary, research on synchromodality and co-modality remains at a formative stage, yet these paradigms are rapidly attracting growing interest across disciplines and sectors. Their integration of digital intelligence, infrastructure sharing and coordinated decision-making offers promising pathways towards a more sustainable and efficient transportation system. The studies collected in this Special Issue provide an initial snapshot of this evolving field – demonstrating conceptual advancement, technological progress and practical experimentation from diverse perspectives. Moreover, emerging modalities such as urban air mobility and the low-altitude economy are beginning to complement traditional transport networks, creating new opportunities for integrated multimodal systems.Looking ahead, several promising directions can guide future research on synchromodality and co-modality. First, the operationalisation of these paradigms should be deepened through large-scale demonstrations and longitudinal case studies that move beyond isolated pilots. Broader cross-sectoral collaborations and open-data initiatives could provide the empirical evidence needed to validate their performance under realistic conditions, revealing how digital coordination, adaptive scheduling and low-altitude transport can function in complex, multi-actor environments.Second, greater attention is required to the institutional and governance dimensions of multimodal integration. Aligning diverse stakeholders – such as infrastructure operators, logistics service providers, public authorities and emerging low-altitude transport operators – remains a critical challenge. Future research may explore incentive design, contractual mechanisms and policy frameworks that can foster cooperation and data sharing while balancing efficiency, equity and environmental goals.Third, the fusion with emerging digital and intelligent technologies will likely accelerate the maturity and adoption of synchromodal and co-modal systems. Integrating Internet-of-Things sensing, digital twins and AI-based decision systems can enhance visibility, synchronisation and responsiveness across transport chains. These technologies also hold promise for improving inclusivity by supporting smaller logistics actors and enabling more adaptive, low-carbon operations, including the efficient integration of low-altitude transport into broader urban mobility networks.