Editorial: A new chapter in logistics research: bridging disciplines, advancing practice

Logistics Research provides an interdisciplinary platform for addressing the volatility, digital transformation and sustainability pressures reshaping modern logistics with innovative, practice-oriented insights. It is a pleasure to announce with this editorial the first issue of Logistics Research published by Emerald. Emerald has been the publisher of this journal since 2025. Logistics Research features original contributions, including theory-driven empirical studies, quantitative modeling applications and technical innovations relevant to logistics. Emphasis is placed on delivering high-quality content that is both rigorous and accessible, ensuring relevance not only to researchers but also to academics and practitioners worldwide. By facilitating knowledge exchange across disciplines, the journal provides a platform for exploring new technologies, management systems and insights across all aspects of logistics.The journal particularly welcomes interdisciplinary approaches to logistics management and engineering, encouraging manuscripts that address logistical challenges at the company, system, or national level. The first issue is a good representation of papers from management (such as Horvat and Lange (2025)) and engineering (such as Carlo et al. (2025)). Contributions that explore emerging, cross-functional, or transformative topics – such as innovative delivery technologies, novel applications (for example, like Poschke et al. (2025)), or new solution methods (for example, like Wolfinger et al. (2025)) – are of special interest. Logistics Research publishes original research that is theoretically grounded and methodologically sound, including empirical, conceptual, quantitative and qualitative studies. The papers in the first issue demonstrate clear practical relevance and a distinctive impact on logistics management and logistics engineering.The focus of Logistics Research is on the practical application of logistics and supply chain management knowledge. In this editorial, we emphasize the real-world relevance of the research published in the journal by providing executive summaries and actionable managerial insights, enabling practitioners and decision-makers to readily understand and apply the latest findings to logistics operations and strategy.From theory to application: Highlights from this issue in Logistics Research. The following three sections showcase exemplary research in logistics, illustrating how Logistics Research bridges rigorous academic inquiry with real-world logistics challenges. From innovations on the warehouse floor to transformations in mobility ecosystems and data-driven resilience strategies, these studies highlight the journal's commitment to interdisciplinary, impactful contributions. Together, they demonstrate how organizations can leverage technology, analytics and strategic insights to enhance safety, efficiency and adaptability across diverse logistics contexts. By presenting these studies with actionable managerial insights, Logistics Research underscores its role as a platform that connects cutting-edge research with practical applications in logistics and supply chain management.The three papers in this section examine how innovative technologies can enhance safety and efficiency in intralogistics while striking a balance between technical and economic trade-offs. Poschke et al. (2025) show that augmented reality can significantly improve forklift safety, though user acceptance hinges on system performance factors such as image quality and latency. Carlo et al. (2025) demonstrate that unidimensional puzzle-based storage systems can reduce automation costs with only limited throughput loss, highlighting how thoughtful design choices can deliver strong cost–performance benefits in warehouse automation. Dilefeld et al. (2025) demonstrate that integrating battery charging directly into the task assignment of automated guided vehicles enables smarter, more efficient fleet scheduling, which reduces unnecessary charging trips, improves availability during peak demand, and ultimately lowers the number of vehicles needed to maintain throughput. Together, the studies demonstrate how human-centered technology design and smart mechanical simplifications and planning can work together to advance safer, more efficient and more affordable intralogistics systems.Poschke et al. (2025) examine a see-through augmented reality (AR) assistance system designed to improve forklift safety by mitigating visibility issues caused by loads and vehicle structures. Through a user study with 18 participants, the paper shows that operators recognize the system’s potential to enhance workplace safety and decision-making. However, acceptance is strongly influenced by technical factors such as image quality and latency.Managerial implications. For managers in intralogistics and warehouse operations, the findings highlight that AR-based driver assistance systems can meaningfully contribute to safer and more efficient handling processes – but only if implemented with sufficient technical maturity. Investments should therefore prioritize high-quality sensor integration, low-latency data processing and robust image rendering to ensure operator trust and reduce training barriers. Additionally, the study suggests that pilot testing with operators is crucial before large-scale deployment, as early feedback can guide targeted improvements and increase adoption. Overall, AR technology offers clear strategic potential for productivity and safety gains, but successful implementation depends on aligning system performance with user expectations.Carlo et al. (2025) examine a new design concept for storage systems – the Unidimensional Puzzle-Based Storage System (UPBS) – where certain grid cells can move loads only horizontally or only vertically, instead of in both directions. This design challenges the traditional assumption that full bidirectional movement is required for efficient PBS operation. Using linear programming models and simulation with decentralized control algorithms, the study evaluates trade-offs between investment cost and operational throughput. The findings show that implementing UPBS can substantially reduce capital expenditures.Managerial implications. UPBS provides managers with a compelling opportunity to reduce automation costs while maintaining acceptable performance levels. By limiting some cells to one-dimensional movement, the authors demonstrate that firms can reduce capital investment by up to 1.8 times the cost of a bidimensional cell, with only an 8.3% average loss in throughput, thereby offering a favorable cost-performance trade-off. The reduced mechanical complexity simplifies system design, maintenance and scalability, while insights from single-escort designs can be confidently applied to multi-escort systems, streamlining implementation. Overall, UPBS strengthens the business case for adopting puzzle-based storage by delivering high-density storage with lower financial risk.Dilefeld et al. (2025) present a new approach to managing automated guided vehicles (AGVs) that integrates battery charging decisions directly into the task assignment process. Instead of treating charging as a separate, inflexible process, the proposed method evaluates charging and task execution simultaneously, improving fleet availability during peak workloads and reducing unnecessary travel to charging stations. Simulation results show that this smarter battery-aware scheduling mechanism can significantly reduce the number of AGVs required to maintain the same throughput, lowering operational costs and energy consumption.Managerial insights. For managers, the key takeaway is that intelligent battery management is crucial for ensuring efficient and continuous AGV operations – especially in dynamic and uncertain production environments. Logistics systems relying on AGV fleets should view battery management as a strategic lever rather than a technical afterthought. Incorporating charging decisions into real-time task assignment helps ensure vehicle availability when demand spikes, while also avoiding excessive opportunity charging that wastes time and power. By reducing redundant charging trips and smoothing fleet utilization, this approach enables companies to achieve the same throughput with fewer robots, directly impacting investment and operating costs. The flexibility of the proposed scheduling logic also means it can be adapted to additional performance criteria, offering a pathway for continuous operational improvement as factories grow more complex and data-rich.The following two papers examine how emerging technologies are reshaping value creation and operational sustainability in the transportation industry. Horvat and Lange (2025) show how autonomous vehicles disrupt traditional roles of logistics service providers and manufacturers, pushing firms toward new platform-based business models, while Oetzel et al. (2025) demonstrate how on-site blending can transform aviation fuel supply chains by improving flexibility, reducing emissions and lowering costs. Together, they illustrate how technological innovation – whether driven by automation or sustainability – requires firms to rethink strategic positioning, operational models and ecosystem partnerships to remain competitive.Horvat and Lange (2025) examine how autonomous vehicles (AVs) are reshaping value creation in the European road transportation sector, focusing on logistics service providers (LSPs) and truck original equipment manufacturers (OEMs). While OEMs are actively expanding into logistics through emerging “Network-Operator” business models – integrating AV-enabled services directly into their offerings – LSPs have largely taken a reactive stance, concentrating on incremental digitalization rather than transforming their business models. This evolving competitive landscape suggests that AV adoption will blur traditional industry boundaries, prompting firms to reassess their strategic positioning, service portfolios and long-term value creation.Managerial implications. Managers in LSPs should proactively explore new AV-enabled service models – such as autonomous fleet orchestration, data-driven coordination platforms or AV-based operational services – to avoid losing relevance as OEMs push downstream. OEMs, in turn, should focus on consolidating platform-based business models that leverage AVs to build long-term, service-centric revenue streams. Both LSPs and OEMs need to invest in advanced digital capabilities, form collaborative ecosystem partnerships and prepare their workforce for evolving skill requirements associated with AV deployment. Firms that adapt early will be better positioned to capture efficiency gains, enhance safety, unlock new value pools and secure competitive advantage in an AV-driven ecosystem.Oetzel et al. (2025) examine the potential of on-site Sustainable Aviation Fuel (SAF) blending at airports as a way to overcome limitations of current pre-blending processes, such as fixed ratios, high transportation costs and long lead times. Using case studies at Singapore Seletar and Maastricht airports, the research finds that postponing SAF blending to the airport level can reduce supply chain costs, lower carbon emissions and offer greater flexibility in customizing fuel blends. The effectiveness of this approach depends on airport-specific factors, including logistics infrastructure, feedstock availability and regulatory conditions, highlighting that strategic airport locations with favorable cost structures are most suited for adoption.Managerial implications. For airport operators and fuel suppliers, implementing on-site SAF blending presents an opportunity to create competitive advantages through cost savings, reduced emissions and increased operational flexibility. Managers should evaluate airport-specific factors, such as infrastructure capabilities, access to feedstock and regulatory frameworks, before adopting the technology. Strategic investment in on-site blending can support sustainability goals, enhance supply chain responsiveness and enable tailored fuel solutions for airlines, making the adoption of SAF more feasible and commercially attractive.The following two papers address complex operational trade-offs that arise under uncertainty, demonstrating how analytical decision-support tools can guide more effective resource allocation. While Berendes et al. (2025) quantify the tension between resilience and efficiency in retail logistics, Wolfinger et al. (2025) tackle similar challenges in pandemic testing operations, showing how dynamic optimization can balance service coverage and infrastructure costs.Retail logistics is experiencing increasing levels of disruption, compelling retailers to strengthen their resilience. Yet, many resilience measures – such as raising safety stock levels – can undermine operational efficiency by driving up costs and reducing performance outcomes. Berendes et al. (2025) introduce a robust and practical approach to evaluate how retail stores balance resilience and operational efficiency in the face of increasing disruptions. By combining data envelopmentanalysis (DEA). With robust optimization, the proposed robust DEA framework provides a quantifiable measure of the resilience-efficiency trade-off. Applying this method to a German retail group reveals that many stores incur substantial efficiency losses to gain resilience, while others manage to maintain both.Managerial Insights. The findings help managers understand how their stores perform relative to their peers and highlight the operational configurations that enable high resilience without incurring excessive costs. Managers can utilize the introduced resilience-efficiency metric to more accurately assess the true cost of resilience initiatives and avoid overinvesting in measures that yield limited value. The results demonstrate that resilience does not inevitably require sacrificing efficiency – certain stores succeed in balancing both, offering valuable reference models for improvement. The framework supports more informed resource allocation decisions, such as whether to prioritize logistics activities or personnel measures, and encourages a strategic perspective that aligns resilience efforts with long-term performance goals. By adopting this approach, retail managers can strengthen their operations against disruptions while preserving or even enhancing efficiency.Wolfinger et al. (2025) address the stochastic dynamic contagious disease testing problem, which arises in pandemic situations such as COVID-19 when suspected cases arrive unpredictably throughout the day. The study develops a Markov decision process model to determine optimal assignments of cases to test centers or mobile test teams, the number and location of test centers, and vehicle routing for mobile teams. Using value function approximation, the authors provide a dynamic policy that balances service coverage of early- and late-known suspected cases with the efficient use of test centers and vehicles. The computational study, based on real-world instances, demonstrates trade-offs between maximizing case coverage and minimizing infrastructure deployment.Managerial implications. For public health authorities and logistics managers, the findings highlight the importance of dynamic and flexible testing strategies during pandemics. Increasing coverage of late-known suspected cases requires investing in additional mobile teams or test centers, but this comes at higher infrastructure and operational costs. Decision-makers can use the proposed decision-support framework to plan daily testing operations, optimize resource allocation, and make trade-offs between cost efficiency and service coverage. The approach provides actionable insights for designing responsive testing logistics that enhance the containment and control of contagious diseases in real-time.The papers featured in this first Emerald-published issue of Logistics Research exemplify the journal's mission to advance both the theory and practice of logistics and supply chain management. From innovations in warehousing, transformative shifts in mobility and data-driven resilience strategies, the research highlights how interdisciplinary approaches can generate actionable insights and have a real-world impact. Collectively, these studies demonstrate the importance of integrating technology, analytics and strategic decision-making to address complex operational challenges, enhance efficiency and create long-term value. Logistics Research continues to serve as a platform that connects rigorous scholarship with practical applications, fostering knowledge exchange that empowers researchers, practitioners and decision-makers to shape the future of logistics.