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This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

The purpose of this paper is to introduce a three-echelon multimodal transportation problem applied to a humanitarian logistic case study that occurred in Mexico.

This study develops a methodology combining a transshipment problem and an adaptation of the multidepot heterogeneous fleet vehicle routing problem to construct a mathematical model that incorporates the use of land-based vehicles and drones. The model was applied to the case study of the Earthquake on September 19, 2017, in Mexico, using the Gurobi optimization solver.

The results ratified the relevance of the study, showing an inverse relationship between transportation costs and delivery time; on the flip side, the model performed in a shorter CPU time with medium and small instances than with large instances.

While the size of the instances limits the use of the model for big-scale problems, this approach manages to provide a good representation of a transportation network during a natural disaster using drones in the last-mile deliveries.

The present study contributes to a model that combines a vehicle routing problem with transshipment, multiple depots and a heterogeneous fleet including land-based vehicles and drones. There are multiple models present in the literature for these types of problems that incorporate the use of these transportation modes; however, to the best of the authors’ knowledge, there are still no proposals similar to this study.

Using building information modelling (BIM) technology, a conventional structure in this study was converted into a green building to measure its energy usage and CO2 emissions.

Digital images of the existing building conditions were captured using unmanned aerial vehicle (UAV), and were fed into Meshroom to generate the building’s geometry for 3D parametric model development. The model for the existing conventional building was created and converted to an energy model and exported to gbXML in Autodesk Revit for a whole building analysis which was carried out in the Green Building Studio (GBS). In the GBS, the conventional building was retrofitted into a green building to explore their energy consumption and CO2 emission.

By comparing the green building model to the conventional building model, the research found that the green building model saved 25% more energy while emitting 46.8% less CO2.

The study concluded that green building reduces energy consumption, thereby reducing the emission of CO2 into the environment. It is recommended that buildings should be simulated at the design stage to know their energy consumption and carbon emission performance before construction.

Occupant satisfaction, operation cost and environmental safety are essential for sustainable or green buildings. Green buildings increase the standard of living and enhance indoor air quality.

This investigation aided in a pool of information on how to use BIM methodology to retrofit existing conventional buildings into green buildings, showing how green buildings save the environment as compared to conventional buildings.

Military and unmanned aerial vehicles (UAV) applications like rocket motor casings, missile covers and ship hulls use components that are made of maraging steel. Maraging steel has properties that are superior to other metals, making it more suitable for the fabrication of such components. A grey relational analysis (GRA) that is based on the Taguchi method has been utilised in the current study to optimise a laser beam welding (LBW) process. Further aspects such as GRA's optimum ranges and percentage contributions were also estimated.

A Taguchi L16 orthogonal array is utilised to design and conduct the experiments. Laser power (LP), welding speed (WS) and focal position (FP) are the three parameters are chosen for the process of welding. The output responses are the upper width of the heat-affected zone (HAZup), the upper width of the fusion zone (FZup) and the depth of penetration (DOP). The effect of the above key parameters on the responses was examined using an analysis of variance (ANOVA).

The results of ANOVA reveal that the parameter that has the most influence on the overall grey relational grade (GRG) is the FP. Finally, metallographic characterisation and a microstructural analysis are conducted on the weld bead geometry to demarcate the zone of HAZ and fusion zone (FZ).

As the most important criteria for LBW of maraging steels is the provision of higher DOP, higher FZ width and lower heat-affected zone, the study intended to prove the applicability of GRA technique in solving multi-objective optimisation problems in applications like defence and unmanned systems.

This study aims to explore the potential use of drones in special library services, aiming to enhance accessibility, services and reliability. It examines how drones can provide library materials to individuals unable to access traditional services and addresses challenges associated with drone implementation.

This study involves a literature review and case studies to analyze the feasibility and benefits of incorporating drones into special libraries. This study also discusses the synergy between drone technology and artificial intelligence (AI) in enhancing library operations.

Drones have the potential to transform special libraries by automating tasks, improving efficiency and expanding outreach. Their application ranges from inventory management and book retrieval to security, surveillance and outreach initiatives. AI-powered drones can provide real-time data on library usage and enhance cost-effectiveness. However, challenges including costs, privacy concerns and regulatory frameworks need to be addressed.

The integration of drones and AI in special library services presents a novel approach to revolutionizing library operations. This study uniquely combines these technologies, emphasizing the importance of proactive consideration of challenges and prospects for successful implementation.

The purpose of the paper is to analyse the sequence of forces acting as barriers in the usage of drones in the construction industry using interpretive structural modelling (ISM). The usage of drones in the construction industry is brought out phase-wise with the help of literature and live cases. Barriers to the usage of drones in construction and steps to derive the interaction between them are described in detail.

The extraction of barriers to the usage of drones in construction is done through cases and supported by the literature. The identification of the interaction between the barriers is done through multi-criteria decision models, namely, ISM and Matriced Impacts Croises Multiplication Appliquee a un Classement (MICMAC) and the results are presented in the form of a hierarchical structure. The paper highlights the potential for the usage of drones in every phase of construction across three stages of construction and eight different applications.

The findings on the interaction between barriers show that technical and research and development-related barriers have a higher driving power, ultimately influencing negativity among stakeholders in drone usage for construction. By analysing interrelationships between barriers, management can frame suitable strategies to adopt drone usage in projects. Awareness about the strength of certain barriers can help management take steps to mitigate the same.

By analysing interrelationships between barriers, management can frame suitable strategies to adopt drone usage in projects. A major limitation is a restriction of the study area to the Indian subcontinent. However, the authors believe that the results can be applied across countries where drone technology is at the nascent stage.

Awareness about the strength of certain barriers can help stakeholders take steps to mitigate the same.

The results of this research also give some inputs to the government’s drone policy for wider usage of drones in the construction industry.

To the best of the authors’ knowledge, most studies on drones in construction industry bring out a list various challenges to their adoption. In this study, the authors have gone further to perform a hierarchical sequencing of barriers to drone adoption based on challenges faced in an emerging economy like India.

Despite extensive academic research related to digital technologies (DT), their integration into architecture, engineering and construction (AEC) projects lags in practice. This paper aims to discover DT deployment patterns and emerging trends in real-life AEC projects.

A case study methodology was adopted, including individual case analyses and comparative multiple-case analyses.

The results revealed the temporal distribution of DT in practical AEC projects, specific DT products/software, major project types integrated with digital solutions, DT application areas and project stages and associated project performance. Three distinct patterns in DT adoption have been observed, reflecting the evolution of DT applications, the progression from single to multiple DT integration and alignment with emerging industry requirements. The DT adoption behavior in the studied cases has been examined using the technology-organization-environment-human (TOE + H) framework. Further, eight emerging trend streams for future DT adoption were identified, with “leveraging the diverse features of certain mature DT” being a shared recognition of all studied companies.

This research offers actionable insights for AEC companies, facilitating the development of customized DT implementation roadmaps aligned with organizational needs. Policymakers, industry associations and DT suppliers may leverage these findings for informed decision-making, collaborative educational initiatives and product/service customization.

This research provides empirical evidence of applicable products/software, application areas and project performance. The examination of the TOE + H framework offers a holistic understanding of the collective influences on DT adoption. The identification of emerging trends addresses the evolving demands of the AEC industry in the digital era.

With the increasing use of small unmanned aircrafts (SUAs), many countries have enacted laws and regulations to ensure the safe use of SUAs. However, there is a lack of industry-specific regulations accounting for the unique features of construction-related SUA operations. Operating SUAs in the construction industry is attributed to specific risks and challenges, which should be regulated to maximize the utility of SUAs in construction. This study, therefore, aims to develop a multi-dimensional regulatory framework for using SUAs in the construction industry.

A combination of quantitative and qualitative methods was used to compare seven selected national/regional SUA regulations to identify the applicability of implementing the existing regulations in construction. The interview surveys were then conducted to diagnose the challenges of construction-related SUA operations and gather interviewees' suggestions on the regulatory framework for SUA uses in construction.

The research found that some challenges of construction-related SUAs operations were not addressed in the current regulations. These challenges included the complex and time-consuming SUA operation permit, lack of regulation for special SUA operations in construction, insufficient regulatory compliance monitoring and a lack of construction-related remote pilots' training. A regulatory framework was then developed based on the findings of comparative analysis and interview surveys.

This study mainly compared seven representative countries/regions' regulations, leading to a small sample size. Further research should be carried out to study the SUA regulations in other places, such as South Africa, South America or Middle East countries. Besides, this study's respondents to the interviews were primarily concentrated in Hong Kong, which may cause the interview results to differ from the construction industry in other countries/regions. A large-scale interview survey should be conducted in other places in the future to validate the current findings.

The proposed regulatory framework provides a reference for the policy-makers to formulate appropriate industry-specific SUA regulations and improve the applicability of SUA regulations in the construction industry. It sheds light upon the future of SUA regulations and the development of regulatory practice in this area.

This study is the first to propose a multi-dimensional regulatory framework for operating SUAs in construction by comprehensive policy comparisons and interviews. The regulatory framework offers a fresh insight into the unexplored research area and points out the direction for subsequent studies on SUA regulations in the construction industry.

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.

The purpose of this study is to evaluate food supply chain stakeholders’ intention to use Industry 5.0 (I5.0) drones for cleaner production in food supply chains.

The authors used a quantitative research design and collected data using an online survey administered to a sample of 264 food supply chain stakeholders in Nigeria. The partial least square structural equation model was conducted to assess the research’s hypothesised relationships.

The authors provide empirical evidence to support the contributions of I5.0 drones for cleaner production. The findings showed that food supply chain stakeholders are more concerned with the use of I5.0 drones in specific operations, such as reducing plant diseases, which invariably enhances cleaner production. However, there is less inclination to drone adoption if the aim was pollution reduction, predicting seasonal output and addressing workers’ health and safety challenges. The findings outline the need for awareness to promote the use of drones for addressing workers’ hazard challenges and knowledge transfer on the potentials of I5.0 in emerging economies.

To the best of the authors’ knowledge, this study is the first to address I5.0 drones’ adoption using a sustainability model. The authors contribute to existing literature by extending the sustainability model to identify the contributions of drone use in promoting cleaner production through addressing specific system operations. This study addresses the gap by augmenting a sustainability model, suggesting that technology adoption for sustainability is motivated by curbing challenges categorised as drivers and mediators.