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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.

Unmanned aerial vehicles are commonly known as UAVs and drones. Nowadays, industries have begun to realise the operational and economic benefits of drone-enabled tasks. The Internet of Things (IoT), Big Data, drones, etc., represent implementable advanced technologies intended to accomplish Industry 4.0. The purpose of this study is to discuss the significant contributions of drones for Industry 4.0.

Nowadays, drones are used for inspections, mapping and surveying in difficult or hazardous locations. For writing this paper, relevant research papers on drone for Industry 4.0 are identified from various research platforms such as Scopus, Google Scholar, ResearchGate and ScienceDirect. Given the enormous extent of the topic, this work analyses many papers, reports and news stories in an attempt to comprehend and clarify Industry 4.0.

Drones are being implemented in manufacturing, entertainment industries (cinematography, etc.) and machinery across the world. Thermal-imaging devices attached to drones can detect variable heat levels emanating from a facility, trigger the sprinkler system and inform emergency authorities. Due partly to their utility and adaptability in industrial areas such as energy, transportation, engineering and more, autonomous drones significantly impact Industry 4.0. This paper discusses drones and their types. Several technological advances and primary extents of drones for Industry 4.0 are diagrammatically elaborated. Further, the authors identified and discussed 19 major applications of drones for Industry 4.0.

This paper’s originality lies in its discussion and exploration of the capabilities of drones for Industry 4.0, especially in manufacturing organisations. In addition to improving efficiency and site productivity, drones can easily undertake routine inspections and check streamlines operations and maintenance procedures. This work contributes to creating a common foundation for comprehending Industry 4.0 outcomes from many disciplinary viewpoints, allowing for more research and development for industrial innovation and technological progress.

Organisations and industries are often looking for technologies that can accomplish multiple tasks, providing economic benefits and an edge over their competitors. In this context, drones have the potential to change many industries by making operations more efficient, safer and more economic. Therefore, this study investigates the use of drones as the next step in smart/digital warehouse management to determine their socio-economic benefits.

The study identifies various enablers impacting drone applications to improve inventory management, intra-logistics, inspections and surveillance in smart warehouses through a literature review, a test of concordance and the fuzzy Delphi method. Further, the graph theory matrix approach (GTMA) method was applied to ranking the enablers of drone application in smart/digital warehouses. In the subsequent phase, researchers investigated the relation between the drone application's performance and the enablers of drone adoption using logistic regression analysis under the TOE framework.

This study identifies inventory man agement, intra-logistics, inspections and surveillance are three major applications of drones in the smart warehousing. Further, nine enablers are identified for the adoption of drone in warehouse management. The findings suggest that operational effectiveness, compatibility of drone integration and quality/value offered are the most impactful enablers of drone adoption in warehouses. The logistic regression findings are useful for warehouse managers who are planning to adopt drones in a warehouse for efficient operations.

This study identifies the enablers of drone adoption in the smart and digital warehouse through the literature review and fuzzy Delphi. Therefore, some enablers may be overlooked during the identification process. In addition to this, the analysis is based on the opinion of the expert which might be influenced by their field of expertise.

By considering technology-organisation-environment (TOE) framework warehousing companies identify the opportunities and challenges associated with using drones in a smart warehouse and develop strategies to integrate drones into their operations effectively.

This study proposes a TOE-based framework for the adoption of drones in warehouse management to improve the three prominent warehouse functions inventory management, intra-logistics, inspections and surveillance using the mixed-method.

construction industry in the Gulf Cooperation Council (GCC) member countries is at the peak as the region is in the stage of developing its infrastructures. Apart from some positive sign of this boost, several other issues have also been developed in the region. One of such issues is the safety of workers at the construction sites. This article, based on a variety of applications of drones in other industrial sectors, considers the use of drones for construction safety improvement in the GCC countries. This article aimed to investigate the safety-related applications of drones considering technical features and barriers and enablers for safety-related tasks.

A mixed research approach using both qualitative and quantitative methods was adopted to achieve the aims and objectives of this research. Data were collected through a systematic literature review, semistructured interviews and using a structured questionnaire. A total of 37 relevant research items and 10 interviews were held with construction safety professionals, and 92 responses collected from the safety managers through a structured questionnaire was used to derive the conclusion of this research. The collected data were processed and analyzed using the Statistical Product and Service Solutions (SPSS) program. Descriptive analyses were carried out in which means and importance factors were calculated.

25.92% of participants confirmed that they or their company had used the drone in different activates. The most common application of drones reported by the respondents was photography for marketing purposes followed by surveying application and quality inspections. The camera movability was the top-rated technical feature required for safety-related inspections. Similarly, “Working near the corner or edge of unprotected opening” was the top-rated application of drone for safety-related tasks. The safety concerns of using drones at job sites were rated as the most important barrier by the participants. Technical challenges associated with the use of drones for safety improvement was rated as the second most important barrier by the participants.

Although, the research presented in this article is based on the GCC construction industry, however, since the data collected through systematic review and semistructured interviews are not a regional base, therefore the finding of this research could also be useful in other regions. Further research however, needs to be conducted to reduce the implications of the barriers identified in this paper so that the drone can be effectively used for safety improvement in construction not only in the GCC region but also in other countries.

Once the GCC construction industry will be able to overcome the challenges associated with the application of drones in safety improvement, the safety managers will be able to monitor the site more effectively which could be helpful to improve the safety performance of the construction organization.

Improved safety performance in not only in the greater interest of the construction organizations as they can reduce the costs associated with poor safety but can also avoid the delay caused by construction accidents. Similarly, improved safety performance reduces the accidents at construction sites, and thus reduces injuries and disabilities caused by such accidents, making the construction workers a useful part of the society. The application of drones in safety-related tasks is one of the key solutions that can lead us to improved safety performance.

Although, the use of drone technology has revolutionized a number of industrial sectors due to its variety of applications, the application in construction particularly in the GCC region is still very limited. As noted in the results of this research, only 21 participants (25.92%) expressed that they or their company had used the drone in different activates. This means that the industry is not getting the full advantage of the available drone technology. The results of this research will enable construction industry stakeholders to know the challenges associated with the application of drones for safety improvement and to develop strategies to overcome these challenges.

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.

This study aims to explore DroneSim, a virtual reality (VR)-based flight training simulator, as an alternative for real-world drone-mediated building inspection training.

Construction, engineering and management students were asked to pilot drones in the VR-based DroneSim space and perform common flight operations and inspection tasks within the spatiotemporal context of a building construction project. Another student group was also recruited and asked to perform a similar building inspection task in real world. The National Aeronautics and Space Administration (NASA)–Task Load Index (TLX) survey was used to assess students’ inflight workload demand under both Real and DroneSim conditions. Post-assessment questionnaires were also used to analyze students’ feedback regarding the usability and presence of DroneSim for drone building inspection training.

None of the NASA–TLX task load levels under Real and DroneSim conditions were highly rated by students, and both groups experienced comparable drone-building inspection training. Students perceived DroneSim positively and found the VR experience stimulating.

This study’s contribution is twofold: to better understand the development stages involved in the design of a VR-based drone flight training simulator, specifically for building inspection tasks; and to improve construction students’ drone operational and flight training skills by offering them the opportunity to enhance their drone navigation skills in a risk-free, repeatable yet realistic environment. Such contributions ultimately pave the way for better integration of drone-mediated building inspection training in construction education while meeting industry needs.

The present study intends to discover and analyze the determinants of users' intention to use (ITU) drone-based online food delivery (OFD) services. The study mainly focuses on the drone-based food delivery system in India and its implications.

This study has used the purposive sampling method. With the support of the technology acceptance model (TAM) and the theory of planned behavior (TPB), a theoretical model was developed conceptually. Later, the model was validated using the partial least square-structure equation modeling (PLS-SEM) technique with consideration of 324 responses mainly from university students in Delhi- National Capital Region (NCR).

The findings reveal that all the determinants are positively and significantly related to ITU, except for perceived behavioral control that does not influence the consumer’s ITU drone-based OFD services. The study also shows that how food delivery system through drone can revolutionize the entire food delivery system in India.

The present study has developed a unique model that can be used by practitioners, future researchers in this field and policymakers in government departments. The present study is limited to Delhi-NCR in India, and thus, there is an issue of generalizability in the present study.

This study has examined the future of food delivery system through drone-based system. Thus, the leaders in the food industry will be better positioned to understand consumers' intentions to use OFD services using drones and be able to make more informed decisions about investment in drone technology in their respective organizations.

The present study has combined both the technology adoption model and the TPB and developed a theoretical model. The study enriches the literature on drone-based OFD services. Since users' acceptance of OFD services using drones is an under-researched area, the present study will make a meaningful contribution to bring the body of literature in this domain.

This paper aims to explore the types of perceived risks involved with using drone food delivery services. Furthermore, this study investigates the relationship between perceived risk and image of drone food delivery services. Lastly, this study examines the effect of image of drone food delivery services on desire, intentions to use and willingness to pay more.

This study collected data from 331 respondents in Korea. Before the start of the survey, the respondents were given a video, which made it easier for them to understand drone food delivery services.

The three types of perceived risks (i.e. time risk, performance risk and psychological risk) have a negative influence on image of drone food delivery services and, thus, aids in increasing desire, intentions to use and willingness to pay more.

The concept of perceived risk was applied to the context of drone food delivery services in this study in combination with other understudied concepts, image, desire, intentions to use and willingness to pay more. This study is one of the first studies that applied those significant concepts to the context of drone food delivery services, even though there are a large number of papers in the technology field. Thus, the findings of this study will be important to foodservice companies when building successful drone food delivery services.

Delivery management of perishable products such as blood in a supply chain is a considerable issue such that the last-mile delivery, which refers to deliver goods to the end user as fast as possible takes into account as one of the most important, expensive and, polluting segments in the entire supply chain. Regardless of economic challenges, the last-mile delivery faces social and environmental barriers to continuing operations while complying with environmental and social standards, therefore incorporating sustainability into last-mile logistic strategy is no longer an option but rather a necessity. Accordingly, the purpose of this paper is to consider a last-mile delivery in a blood supply chain in terms of using appropriate technologies such as drones to assess sustainability.

The authors discuss the impact of drone technology on last-mile delivery and its importance in achieving sustainability. They focus on the effect of using drones on CO₂ emission, costs and social benefits by proposing a multi-objective mathematical model to assess sustainability in the last-mile delivery. A preemptive fuzzy goal programming approach to solve the model and measure the achievement degree of sustainability is conducted by using a numerical example to show the capability and usefulness of the suggested model, solution approach and, impact of drone technology in achieving all three aspects of sustainability.

The findings illustrate the achievement degree of sustainability in the delivery of blood based on locating distribution centers and allocating drones. Moreover, a comparison between drones and conventional vehicles is carried out to show the preference of using drones in reaching sustainability. A sensitivity analysis on aspects of sustainability and specifications of drone technology is conducted for validating the obtained results and distinguishing the most dominant aspect and parameters in enhancing the achievement degree of sustainability.

To the best of the authors’ knowledge, no research has considered the assessment of sustainability in the last-mile delivery of blood supply chain with a focus on drone technology.

The purpose of this paper is to analyze the factors affecting the implementation of unmanned aerial vehicles (UAVs) in Indian humanitarian logistics. The factors listed are significant as they are hindering the incorporation of this new technology into the humanitarian supply chain, thus creating inefficiencies in the humanitarian logistics sector.

This research is approached using a two-step process. In the first step, the particular barriers for UAV implementation are determined by a literature review and consultation with experts. Next, the proposed framework, a combination of grey-decision-making trial and evaluation laboratory (grey-DEMATEL) and analytic network process (ANP), i.e. g-DANP, is used to determine a hierarchical structure for the factors and sub-factors. The grey hypothesis provides sufficient analytical data to an otherwise lacking DEMATEL technique. Also, the use of ANP gives weightage to each factor, allowing us to categorize their importance further.

This study reveals that factors like expensive commercial solutions and high transport energy costs are significant factors of the “cause” group, whereas the uncertain cost for maintenance and repair and deficiency of high-level computing are crucial factors of the “effect” category. The mentioned factors, along with many others, are the main reasons for the delayed incorporation of UAVs in humanitarian logistics.

The results of this study present insights for humanitarian supply chain managers, UAV producers and policymakers. Those in the humanitarian logistics sector can use the findings of this study to plan for various challenges faced as they try and implement UAVs in their supply chain.

This research is unique as it analyses the general factors hindering the implementation of UAVs in Indian humanitarian logistics. The study enriches existing literature by providing an analytic approach to determine the weightage of various interrelations between the identified factors affecting UAV incorporation in the humanitarian supply chain.