Drone Delivery Service Research Articles

Consumer support for restrictive policies on unhealthy food and beverage delivery via drones.

Drone delivery services are set to increase unhealthy food and alcohol accessibility. The aim of this study was to evaluate public receptiveness to various options for regulating drone food and beverage deliveries and to identify sociodemographic differences in receptiveness. In total, 1079 adults were surveyed to assess total support and differences in support between population subgroups (e.g.age, sex, location, existing habits) for nine potential drone policies covering curfews, quotas, and product bans. Support was measured on five-point agreement scales, with mean individual policy support (M) and grand mean support calculated for all assessed policies (grand M). There was moderate support for all assessed policies (grand M=3.5), ranging from M=3.2 (drone delivery quotas for shopping centres and dwellings) to M=3.7 (night curfews, airspace quotas). Factors associated with policy support were older age, metropolitan residenceand using grocery delivery services. Public support exists for policies designed to restrict drone food and beverage deliveries. Drone food and beverage delivery policies will likely be supported by the public and could assist in controlling the accessibility of such products for the benefit of population dietary health.

텍스트마이닝을 활용한 도심 드론 물류 서비스 수용성에 대한 연구: 유튜브 댓글을 활용하여

In modern society, logistics systems need new innovations due to urban traffic congestion and environmental issues. Drones, or unmanned aerial vehicles, are gaining attention for improving urban logistics efficiency. However, drone delivery faces issues such as costs, regulations, and noise. This study analyzes consumer perceptions of drone delivery services using text mining technology. A total of 16,695 comments from 587 YouTube videos containing the keyword ‘drone delivery’ were analyzed through frequency analysis, topic modeling, and sentiment analysis. The results provided insights into consumer opinions, attitudes, concerns, and preferences regarding drone logistics. Major issues identified include potential accidents, noise, and high costs. Proposed solutions include enhancing safety, developing noise reduction technologies, reducing costs, and achieving social consensus. This study offers insights for improving drone delivery services and developing strategies that reflect consumer demands for future implementations.

Shortening The Last-Mile: Impact of Zipline Medical Drone Delivery on The Operations of Hard-to-Reach Healthcare Facilities in Northern Ghana.

Purpose: This research study investigated the impact of Zipline Medical Drone Delivery on the operations of last-mile healthcare facilities in northern Ghana. Design/Methodology/Approach: The research study adopted an exploratory research design to determine the impact of Zipline’s medical drone delivery on the operations of last-mile healthcare facilities in Northern Ghana. An online survey questionnaire was deployed to collect quantitative data from 159 trained employees of last-mile health facilities who were selected through a purposive sampling technique from last-mile drone-served healthcare facilities. Findings: The study established that drone delivery speed, logistics efficiency and availability of drone delivery resources significantly impacted zipline delivery of medical commodities to last-mile public healthcare facilities in Northern Ghana, reducing commodity delivery lead-time and improving access to essential healthcare supplies for efficient service delivery. Research Limitation/Implications: This research focused mainly on the impact of drone delivery of medical commodities on the operations of last-mile public healthcare facilities in Northern Ghana. Practical Implications: The results of this study show that by enhancing drone delivery speed, logistics efficiency and drone resource availability, the operations of public healthcare facilities can be improved by ensuring that essential medicines are made available, patient waiting time is significantly reduced and outpatient services are improved. Social Implication: The study recommends the establishment of a Zipline-Administrators partnership which will eventually result in a reduction of medical commodity lead-time, improved accessibility of patients to essential health commodity supplies and general cost savings to the community. Originality/Value/Novelty: Although drone technology has been the subject of numerous studies in Ghana, none has investigated the impact of medical commodity drone delivery services on the operations of last-mile healthcare facilities in Northern Ghana. This study therefore explored the impact of drone delivery services from the last-mile healthcare facilities’ perspective.

Integrated truck drone delivery services with an optimal charging stations

Battery-powered drones, or unmanned aerial vehicles (UAVs), present significant market potential for faster, economical, and eco-friendly urban delivery solutions. Many firms are investing in drone logistics ventures to capitalize on their capabilities. However, the limited range of drone deliveries, dictated by battery capacity, poses a significant challenge. Hybrid delivery systems combining trucks and drones have gained attention to overcome this challenge. Traditional models assume trucks park at customer sites while drones handle additional deliveries, yet this approach may hinder drone efficiency due to constraints in parking availability. Alternative approaches like battery swapping and mobile charging stations on trucks have been explored but exhibit limitations such as blind spots and substantial battery reserves. We propose establishing dedicated drone charging stations and optimizing drone routing for efficient deliveries to address these issues We present a MINLP (Mixed Integer Non-Linear Programming) model aimed at identifying the most cost-effective solution that optimizes both transportation efficiency and charging infrastructure investment. Quantitative experiments demonstrate the efficacy of this approach, alongside sensitivity analysis aiding economic decision-making across various operational scenarios. Notably, our experiments show a 15% reduction in total costs when extending the operational lifespan of charging stations from 2 to 4 years.

Exploring Drone Classifications and Applications: A Review

This comprehensive review explores different types of drones and their multifaceted applications across various industries. Investigating diverse sectors, from military use to planetary exploration and delivery services, this comprehensive review thoroughly explores the versatility and utility of fixed-wing, multi-rotor, hybrid, and flapping-wing drone configurations across various industries. The investigation of military drone technologies highlights their evolution from historical deployment in early warfare to modern applications in surveillance and targeted operations. Additionally, the study shows the critical role of drones in space exploration, emphasizing their adaptability in exploring celestial bodies like Mars and Venus. Moreover, the rising interest in drone delivery services is showcased through innovative designs deployed by global companies. This review not only demonstrates the versatility and innovative potential of drones but also presents insights into their practical use and advancements in addressing distinct operational needs across various industries.

A Drone-Driven Delivery Network Design for an On-Demand O2O Platform Considering Hazard Risks and Customer Heterogeneity

Nowadays, the online-to-offline (O2O) retailers provide on-demand delivery service for online orders by their own fleets and riders. An intelligent delivery network lays an important foundation to support cost-effective delivery service in the long run. Drones have great potential to revolutionize the instant delivery industry regarding cost and timeliness, while the hazard risks to humans and the environment should be seriously considered through sophisticated network design. In this paper, we propose a framework for a drone-driven intelligent delivery network design problem with the consideration of the multi-dimensional risk map, which needs to determine store location, drone fleet size and allocation, customer assignment, customer delivery mode selection, and delivery routing. A bi-objective non-linear programming model is formulated to maximize profit and minimize integrated risks as well. To tackle large instances, a modified NSGA-III algorithm is developed, which is incorporated with problem-specific search operators and Pareto local search to obtain Pareto solutions efficiently. Real-world data-based numerical experiments are conducted to verify the performance of the modified NSGA-III algorithm compared to the modified NSGA-II. A case study based on the geographical information in Shanghai is analyzed to validate the effectiveness of the proposed model. Moreover, sensitivity analysis is presented to evaluate the effects of multiple parameters on the drone delivery service network design. Some managerial insights are obtained for the O2O retailer who offers on-demand delivery service through online platform.

Consumers’ perceptions of the environmental and public health benefits of last mile drone delivery

ABSTRACT Using Technology Acceptance Model, Theory of Planned Behavior, and Privacy Calculus as theoretical frameworks, this study examined environmental and public health/safety dispositions and environmental and public health/safety benefits, perceived usefulness, privacy risk, and trust as they relate to U.S consumers intention to adopt drone delivery services. This study employed Partial Least Squares – Structural Equation Modeling methods and data were collected online using Amazon Mechanical Turk, resulting in 687 respondents. The results show that the intention to use drones for delivery increases if consumers perceive drone delivery to be useful. Additionally, perceived usefulness was influenced by a person’s environmental and public health/safety dispositions along with related benefits. Additionally, as a person’s perceived usefulness increases their perceived privacy risk decreases. Further, this study found that organisational trust moderates the negative effect of privacy risk on drone adoption.

“Amazon Clone”

Amazon, the world's largest online retailer, has continually evolved to meet the changing needs and expectations of consumers. In the wake of the digital age, where convenience and personalization reign supreme, Amazon is poised to embark on its next transformative journey - Amazon 2.0. At the core of Amazon 2.0 lies a commitment to innovation and personalization. Leveraging advanced machine learning algorithms and big data analytics, Amazon aims to create a hyper-personalized shopping experience for each user. By analyzing past purchase behavior, browsing history, and demographic information, Amazon can deliver tailored product recommendations that resonate with individual preferences, leading to increased customer satisfaction and loyalty. Furthermore, Amazon 2.0 seeks to redefine the boundaries of convenience through seamless integration of emerging technologies. From voice-activated shopping assistants to drone delivery services, Amazon is at the forefront of revolutionizing the e-commerce landscape. By embracing cutting-edge technology, Amazon aims to streamline the shopping experience, making it faster, easier, and more intuitive for users worldwide. In addition to enhancing the consumer experience, Amazon 2.0 places a strong emphasis on sustainability and social responsibility. Through initiatives such as Amazon's Climate Pledge and commitment to renewable energy, Amazon is working towards a more sustainable future while also giving back to the communities it serves. In summary, Amazon 2.0 represents a bold new chapter in the company's storied history. By embracing innovation, personalization, and sustainability, Amazon is poised to redefine the e-commerce experience and set new standards of excellence for the industry as a whole. Keyword: Amazon Shopping, Retailer, Sales, Purchase

A distributed route network planning method with congestion pricing for drone delivery services in cities

Unmanned aerial vehicle (UAV)-based commercial services, exemplified by drone delivery, have captured wide interest in tech companies, entrepreneurs, and policymakers. Structured route-based UAV operations have been implemented for traffic management of UAVs in support of commercial delivery services in cities. Yet, its essence, multi-path planning with constraints is not well solved in the existing literature. Centralized planning might result in inefficiencies and unfairness in the allocation of precious urban airspace to individual routes. This paper describes a novel distributed route planning method to support UAV operations in a high-density urban environment. The method allows each origin–destination (OD) pair to compete against other OD pairs for an optimized route (e.g. shortest distance), coordinated by a system-level evaluation, leading to a network design that maximizes the performance of not only the individual routes but also the entire system. The core concept is the introduction of congestion pricing, a soft constraint to coordinate the allocation of airspace. The method is tested in standard 2D scenarios and compared with other state-of-the-art methods. The results show that (1) the method is able to generate routes with short individual distances as well as occupying the least airspace by the route network; (2) in some complex scenarios, the method is able to find a solution in a short period of time while other state-of-the-art method fails. The method has also been applied to a real urban environment (Mong Kok in Hong Kong) to demonstrate its capability.

Sorry for the Delay: How FAA Regulations in the U.S. are Stifling Innovation and Hindering the Growth of a Promising New Industry Based on Delivery Drones

From the creation of the transistor radio to robots powered by artificial intelligence, the rapid pace of technological advancements in a multitude of industries has ushered in an innumerable amount of economic, environmental, and social benefits that have collectively produced positive effects around the world. However, in addition to benefits, these rapid advancements in technology have created a particular problem affecting many industries in the United States—antiquated regulations that were promulgated for a particular industry become inefficient and impractical due to rapid technological advancements within that industry. The delivery drone industry, a blossoming new sector of air commerce that has grown exponentially in the past decade, has become the latest victim of regulatory stagnation. The Federal Aviation Administration (FAA) currently regulates commercial delivery drone operations in the U.S. by issuing highly restrictive Part 135 certifications that attach a variety of operating limitations to companies’ delivery drones, such as restricting the traveling distance and airspace location. If companies want to conduct any drone deliveries that fall outside of the strict limitations set by Part 135 certifications, which is the only way to expand their operations to an appropriate commercial scale, those companies must receive exemptions and waivers from the FAA. However, the FAA grants these crucial exemptions and waivers on a case-by-case basis with standards and limitations that vary drastically from company to company. As a result, the FAA has created an unpredictable regulatory minefield that has hindered the expansion of delivery drone operations in the U.S., thus deterring innovation within the drone industry as a whole. Rather than accepting regulatory standards that inhibit the growth of an entire industry, the FAA should adopt a streamlined, standardized certification and approval process for delivery drones that efficiently facilitates the advancement of commercial delivery drone operations in the U.S. This Comment examines the various issues plaguing the current regulatory framework for commercial drone delivery services within the U.S. and seeks to provide a possible solution to these obstructionist regulatory standards through the adoption of a streamlined regulatory scheme for commercial delivery drones. To conduct a full analysis on this topic, this Comment first examines the historical development of the FAA’s current regulations governing commercial drone delivery services, addresses how the current case-by-case exemption process established by the current regulatory regime places an illogical hindrance on the growth of a blossoming industry, and highlights other specific problems plaguing the current regulatory process, echoed by the outcries of various drone industry stakeholders. Additionally, as an alternative solution to the current piecemeal regulatory regime, this Comment argues that Congress, and subsequently the FAA, should adopt the Increasing Competitiveness for American Drones Act of 2023 (American Drones Act) that creates a comprehensive, streamlined regulatory framework for drone delivery services. Finally, this Comment explains how the adoption of the American Drones Act would produce various economic, environmental, and social benefits for millions of individuals across the U.S.—such as the ability to efficiently scale BVLOS drone operations, emissions reduction, and increased consumer access to healthy foods and vital medicines.

Consumer Preferences and Barriers in the Adoption of Drone Delivery Services: A Comprehensive Analysis

Consumer Preferences and Barriers in the Adoption of Drone Delivery Services: A Comprehensive Analysis

Scheduling‐location problem with drones

AbstractDrone operation, a new driving force for logistics innovation, is struggling to overcome practical challenges. One of the concerns for drone utilization is limited flight ranges, and different concepts of facilities are continually developed to support drone delivery. These new facilities prompt the need to integrate decision‐making across different phases. In particular, the deployment of facilities that complement the physical limitations of drones and the scheduling of drones to perform delivery tasks are closely related. Therefore, we developed a scheduling‐location problem with drones, a new methodology for integrating operational and strategic planning decisions. The integrated decision‐making determines the location of the drone facilities by not only considering the critical distance of facilities but also by taking into account whether the delivery schedule is implemented. In our model, additional drone facilities are sometimes opened considering available drones due to the feasibility of the delivery schedule. An extended formulation and a restricted master heuristic are proposed to solve problems time‐efficiently. Computational results show that the restricted master heuristic outperforms the mathematical model in finding solutions for large‐scale instances. The developed model and heuristic algorithm provide drone delivery services even in areas that are not easily reachable by drones due to being located far from the warehouse and can be effectively applied to humanitarian logistics.

Examining urban delivery service user profiles and determinants of drone delivery adoption in Ghana considering usage before and after the COVID-19 pandemic

The demand for urban delivery services (UDS) in low- and middle-income countries (LMICs) has been growing due to the spike in e-commerce activities. This phenomenon has led to the search for more innovative UDS modes, such as drones, as they provide fast, safer, and eco-friendly services. Although researchers have examined the perceptions regarding the adoption of drone delivery, there are many unknowns about the intentions to use this futuristic delivery mode. By employing survey data obtained through an online survey conducted in Ghana, this study aims to gain a deeper understanding of the current UDS user profiles and investigate their intentions to adopt drone deliveries in the future, considering the lived experiences of traditional UDS usage pre/post the COVID-19 pandemic. Regarding UDS user profiling, the study applied an advanced unsupervised machine learning method known as cluster correspondence analysis to simultaneously identify critical clusters in the data as well as key factor associations for each group. The findings demonstrated that most people in Ghana who seldom used the traditional UDS usually experienced poor service levels. Females living in the capital of Ghana who are frequent users of UDS mainly experienced acceptable service levels. Using an ordered probit regression model, the study identified that variables such as males, people who desired contactless UDS, and frequent UDS users at work or school during the COVID-19 pandemic were more inclined to embrace drone deliveries when introduced. Conversely, individuals who frequently used UDS services at home, those living in large cities, and those with lower income levels expressed reluctance toward drone delivery services. This study augments the urban logistics literature in LMICs by offering insightful suggestions in the areas of education, enhanced marketing strategies, and delivery optimization, which are instrumental for informing policy decisions. Government-related transportation bodies, private logistics firms, and trade unions can collaborate and adopt the recommendations provided to improve urban delivery services and to pave the way for integrating drone delivery services in the near future.

Drone delivery and the value of customer privacy: A discrete choice experiment with U.S. consumers

Drone delivery services are becoming increasingly available, but they introduce new consumer privacy risks. As a result of safety regulations that require drones to broadcast their locations, third-party observers may link customers to their purchases by following a delivery from vendor to customer. These privacy risks can be reduced with routing strategies that aggregate customer orders, at the potential cost of additional delivery wait times or fees. This study measures the importance of these privacy risks to delivery service customers, their willingness to pay for privacy, and how this differs across consumer groups and product types. We developed a discrete choice experiment and mode choice logit models using data from over 3700 U.S. consumers who chose between ground vehicle versus drone delivery across a range of privacy, delivery fee, and wait time options. Preferences were tested for various product types: take-out food, liquor store items, groceries, and prescription medications. Results show offering privacy enhancements significantly increased consumers’ likelihood of choosing drone delivery. Without privacy enhancements, when fees and wait times were the same, consumers chose ground vehicle 4 times more often than drone. Offering privacy for the drone option closed this gap. Yet preferences differ by demographic group. Males and frequent e-commerce users were more likely to prefer drone regardless of privacy, while privacy improvements had a significantly larger impact on females and younger consumers. We measured consumers’ value of privacy in both money and time. The value of privacy for medications delivery was about twice that for other product types. The value of privacy was then highest for liquor store items, then groceries, then take-out food. Our results can inform delivery service planning as well as contribute to a broader understanding of how consumers value privacy and methods to measure that valuation.

Switching up the delivery game: Understanding switching intention to retail drone delivery services

Drone delivery services have been gaining momentum in retail due to the surge in digital commerce, and retail giants are seen making significant progress in delivering parcels with minimal human intervention. However, the wider diffusion of drone delivery services requires an in-depth understanding of consumers' switching intention from traditional delivery services to drone delivery services. To address this gap, the present study aims to propose and validate an asymmetric model encompassing innovation barriers, shopping motivations, and individual differences (i.e., inertia and affinity for technology interaction) in understanding consumers’ switching intention. An online survey was conducted. The data was analyzed using fuzzy set qualitative comparative analysis (fsQCA). The results revealed five configurations with different combinations of causal antecedents.

The Impact of Drone Delivery Innovation on Customer Intention: An Empirical Study in Vietnam

Since e-commerce in the world is becoming increasingly popular, it leads to an increase in demand for a more efficient delivery system. Drone delivery innovation, with its distinct attributes, is contributing several advantages for delivery services. This paper studies the impact of drone delivery services on customers’ intention in Vietnam. The research uses correlation analysis and structural equation modeling (SEM) to analyze the data of 405 valid observations collected in a structured questionnaire survey in Vietnam. The paper reveals that convenience, speed, and compatibility affect customers’ attitude while convenience and compatibility have no negative effects on costs. Convenience has the highest impact on customers’ attitude, while speed concern has the lowest impact. In regard to customers’ intention to use drone delivery services, attitude has a strongly positive impact, while costs have a negative influence.

Upcoming drone delivery services: A perceptions-based clustering of citizens in Lisbon

Drones are an emerging technology that promises numerous benefits for delivery services. As e-commerce evolves and citizens become more familiar with parcel delivery services to their homes, drone services could become an alternative for last-mile logistics service providers. However, the potential diffusion of drone services will also be influenced by the public opinion. This study addresses the issue of citizens' perceptions of drone delivery services and uses the Metropolitan Area of Lisbon as a case study. Data was collected though a survey and analysed using a clustering approach. Six citizen clusters were identified: the drone-service supporters, the concerned about the package, the concerned with legal aspects, the drone-service neutrals, the likely supporters, and the non-supporters. The clusters vary according to socio-economic characteristics and members’ current satisfaction with the home delivery services. Logistics stakeholders can use the results of this study to successfully introduce drones into their logistics systems and benefit from the added value to the public.

Increasing the intention of Gen Zers to adopt drone delivery services based on a three-step decision-making process

Generation Zers are digital natives who may be early adopters of drone delivery services for e-commerce. Therefore, e-commerce vendors must understand what causes Gen Zers to believe, desire, and intend to adopt drone delivery services. Gen Zers were surveyed regarding their decision-making processes using the DITTO research framework (Diversity, Individualism, Teamwork, Technology, and Organizational Support) and belief-desire-intention theory. A survey was conducted with 83 Gen Zers from the United States, and data was analyzed using multilinear regression analysis. Many important implications can be drawn from the analysis results. Before Gen Zers adopt drone delivery services, the “seeing is believing” moment appears to be essential, according to the analysis. Moreover, e-commerce vendors should emphasize drone delivery’s relative advantages in terms of speed and environmental protection. Based on our findings, Gen Zers are rational decision-makers when it comes to adopting drone delivery services. To motivate Gen Zers to use drone delivery services, it is imperative to help them develop the belief and increase their desire.

The drone delivery services: An innovative application in an emerging economy

The rapid development of the Internet of Things (IoT) devices led to new era in the maritime and road transportation industry and research. This article studies the critical determinants of Drone delivery services (personal innovativeness, outcome expectancy, positive anticipated emotions, and perceived risk) on customer willingness to use Drone in an emerging economy. The article employs correlation analysis and structural equation modeling (SEM) to analyze the data of 602 valid observations collected in the structured questionnaire survey in Vietnam. Empirical results indicate that outcome expectancy and personal innovativeness positively impact customer attitude and anticipated emotion, while outcome expectancy has the strongest influence. These findings also show that outcome expectancy and personal innovativeness have an effect on customer willingness to use Drone through their positive attitude and positive anticipated emotions. Interestingly, the perceived risk of Drone is considered a moderator in reducing the relationship between customer attitude and willingness to use Drone while it has an insignificant impact on customer emotion and willingness to use.

Urban drone adoption: Addressing technological, privacy and task–technology fit concerns

Cutting-edge technologies are changing the operations of urban last-mile delivery. In particular, innovative technologies, such as delivery drones, have shown promising results in commercial applications. When considered alongside the ongoing pandemic, contactless technologies have become even more important to the daily lives of consumers in highly urbanized areas. This study investigates underlying factors influencing consumers' acceptance of drone delivery in urban cities amidst the COVID-19 pandemic. To this end, a model was created by fusing the technology acceptance model, task–technology fit, and privacy calculus theory. Four hundred and fifty survey responses were analyzed using structural equation modeling. The findings suggested that perceived usefulness, attitude, and perceived privacy risks directly influence consumers' behavioral intentions. In addition, perceived ease of use, task characteristics, technology characteristics, task–technology fit, and privacy concerns indirectly impact consumers' behavioral intention. This study offers an insightful perspective on consumers’ perception of urban last-mile delivery drones while providing insights into urban transport planning and regulation of drone delivery services.