Last-mile Delivery Research Articles

Ensuring Vaccine Temperature Integrity: Monitoring from Storage to Last-Mile Delivery

Ensuring Vaccine Temperature Integrity: Monitoring from Storage to Last-Mile Delivery

The Role of Last-Mile Delivery Quality and Satisfaction in Online Retail Experience: An Empirical Analysis

The rise of the e-commerce industry has markedly changed the global economy, providing customers with unparalleled access to goods and services. This study empirically examines online shoppers’ perceptions and preferences, focusing on their experiences with last-mile delivery (LMD) services and its impact on their shopping behaviour. This research employs machine learning classification and regression models for a large-scale analysis of customers’ responses, collected using an online survey in the main cities in Saudi Arabia, which is experiencing rapid e-commerce growth amidst a broader digital transformation. The findings highlight a strong consumer preference for timely LMD services, typically within a day of purchase, while noting dissatisfaction with exceedingly early delivery windows. The research emphasises the need to address customer dissatisfaction with delivery services to retain clientele, as many may switch retailers without informing the retailers. Additionally, a considerable trend towards preferring digital over cash-on-delivery payment methods was observed among online shoppers. Overall, this study provides valuable insights into the significant influence of LMD services on customer satisfaction and behaviour in the e-commerce sector. The use of robust machine learning models has revealed critical factors that can guide retailers and LMD providers in enhancing service delivery and customer experience, contributing to the broader discourse on e-commerce logistics efficiency and customer satisfaction.

The Intention to Adopt Parcel Lockers as A Last-Mile Delivery Services in Malaysia

Last-mile delivery serves as the final connection between the upstream supply chain operations and the end consumers, acting as the ultimate link in the supply chain. Research indicates that the logistics sector has experienced significant financial gains as a result of the swift growth of online commerce. Nevertheless, there has been much attention given to the difficulties that accompany the potential benefits of parcel lockers. To overcome the limitations of conventional last-mile logistics in various distribution scenarios and to update the delivery service concept with advanced technology, the implementation of self-collection services is necessary. This research aims to utilize the Theory of Planned Behavior to investigate consumers' preferences in adopting parcel locker services. Specifically, the study seeks to identify the patterns and dimensions of consumer preferences, such as convenience, reliability, relative advantage, and complexity. Additionally, the research examines the mediation effect of customers' attitudes towards parcel locker services in determining their intention to adopt this service. The data was gathered via Google Forms from 138 participants situated within Malaysia. The study's hypotheses were tested using the Statistical Package for the Social Sciences (SPSS) version 27.0. The results indicated that consumer preference which comprise of convenience, reliability, relative advantage, and complexity, had a substantial impact on consumers' sentiments towards parcel locker service. Furthermore, the results indicated that the attitude towards parcel locker service acts as a mediator in the relation between consumer preferences and the intention to utilize parcel locker service. Therefore, this research contributes to the growing body of knowledge on parcel locker services in Malaysia, a topic that is still in its early stages in the country. This enhances the value of the research findings and is highly relevant to bridge the gap in the emerging literature on parcel locker service in Malaysia.

Coordinated last-mile deliveries with trucks and drones: A comparative study of operational modes

Throughout the recent decade, drone delivery technology has been developed to address problems such as last-mile delivery and recurrent traffic jams in metropolitan regions. To resolve the relatively short travel range and limited capacity issues of drones, researchers have proposed to further enhance the utility of drones by deploying them with ground vehicles (e.g., trucks) in tandem. This new concept leads to a new transportation planning problem, i.e., coordinated delivery of trucks and drones (CDTD). In this paper, we conduct a comparative study of three representative operational models: the flying sidekick traveling salesman problem (FSTSP), the traveling salesman problem with drone (TSP-D), and the parallel drone scheduling traveling salesman problem (PDSTSP). Metrics including delivery efficiency and vehicle utilization rate are evaluated for the three models under various scenarios, to extract insights on which operational model is advantageous for which scenario. We also benchmark the algorithms for CDTD by various metrics including result quality, runtime and scalability, and conduct sensitivity analysis to assess the performance of the system under various system parameters, including drone speed, drone range and customer geographic distribution. Finally, a case study is conducted to demonstrate the superior performance of CDTD model as compared to classical TSP model based on real-world data. Experimental results demonstrate that the FSTSP and TSP-D highlight superior performance over PDSTSP and truck-only TSP when the majority of customers are out of the flight range of drone and the customer demand is clustered, as a result of the synchronization and compensation for limitations between the two types of vehicles.

The economic impact of crowd-shipping based on public transport in Egypt: a GA approach.

The last-mile delivery challenges and complexity are increasing simultaneously with the e-commerce growth, the e-commerce growth constitutes a threat to urban transport, especially for big cities and developing countries. This paper examines the economic impact of crowd-shipping based on public transport collaborated with the automated parcel locker and the impact of traditional delivery, as two different methods of last-mile delivery under the same circumstances. This paper aims to assess crowd-shipping as an alternative solution for last-mile delivery compared to traditional delivery. Data has been simulated based on Cairo reality, one of the largest cities in the world. The mathematical models were formulated for the problem, where the first model objective function minimizes the costs of vehicle possession and vehicle kilometers traveled, while the second model objective function minimizes the costs of establishing lockers, vehicle possession, and vehicle kilometers traveled. A genetic algorithm has been used due to the complexity of the problem. The results show that the economic impact of the crowd-shipping delivery system is better than the traditional delivery system under the conditions of large-sized and medium-sized demand, while the economic impact of traditional delivery is better than the crowd-shipping delivery system under the conditions of small-sized demand.

Green Wheels, Greener Wallets: Economic Viability of Last-Mile Delivery Fleet Electrification in Case of Latvia

The analysis of internal combustion engine vehicle (ICEV) usage habits in the DPD Latvija company and the study of the specifics of its last-mile delivery transport business will allow to understand whether electromobility solutions can make the company more efficient. The question addressed in the research is whether the electrification of the delivery vehicle fleet can reduce transport expenses for the company and under what conditions. For estimation of direct and indirect costs of transport acquisition and usage Total Cost of Ownership (TCO) is used. The company’s daily operation parameters and technical data of the used vehicles VW e-Crafter and VW Crafter 35 Kasten/long base are considered in the study. Net Present Value (NPV) and Internal Rate of Return (IRR) calculation methods are used for analyzing the investment project. The expense of the creation of electrical vehicle charging infrastructure is not considered, because the company’s daily routine allows to cover all charging processes overnight by using domestic sockets together with Mode 2 chargers. All technical data and calculations were made for deliveries in a city cycle. In financial terms of owning delivery transport, the company is using a 5-year operational lease with 0% first payment. The obtained results in terms of TCO comparison showed a slight advantage by using EV after 5 years of last-mile delivery service per 1 vehicle – 706.98 Euro at 31200km a year or 100km in the working day of 6-day working week (156000km in 5-year is under 160000 warranty condition). The calculation is performed for DPD Latvija 213 ICE vans of a total 240-vehicle fleet. Results of NPV, NPVI, and IRR with a comparison rate of 10.6% for EV case clearly show a sufficiently good return. The Net Present Value of the solution is 89271.92 Euro and the Internal rate of return is 48.05%. The study proves that the electrification of the last-mile delivery company's fleet is economically justified and within 5 years. In the process of electrification, the company will reduce its expenses – by 1.45%, which increases the net annual profit by 0.13%. The main conclusion is that the company will not incur losses by switching to an environmentally friendly vehicle, the capital investment in a realistic scenario pays off already from the 3rd year. Nevertheless, the authors of the study recommend evaluating delivery vehicles with higher driving range parameters, because during peak delivery and seasons with cold weather, the company may experience unplanned downtime and expenses due to the need for additional charging time at public charging networks on the road, that could lead to financial losses and need for TCO calculation corrections.

Sustainable Solutions in E-Commerce: An Examination of Customer Acceptance of Automated Delivery Stations in Vietnam

The rapid emergence of e-commerce in Vietnam has resulted in significant pressure on freight traffic and the environment, particularly in urban areas. Automated delivery stations (ADSs), also known as smart lockers or parcel lockers, offer a promising solution to improve the sustainability of last-mile delivery systems. However, the adoption of such a sustainable alternative by Vietnamese customers is inadequately understudied. This study primarily aims to investigate factors impacting Vietnamese customers’ acceptance of these automated delivery points. Utilizing structural equation modeling (SEM), a survey following convenience sampling was carried out in Vietnam to assess recent experiences at automated delivery stations. The results showed that innovativeness and location convenience positively influenced consumer intention to use ADS, while perceived time pressure had no impact on consumer intention to use automatic delivery systems. This study provides valuable insights to e-commerce companies to customize their services to match customer preferences, which will optimize last-mile delivery options and thereby promote sustainable practices.

Why and Why Not? Systematic Review of the Willingness to Accept Drone and Robot Deliveries

Last-mile deliveries using drones and robots have recently emerged as alternatives to deliveries using conventional trucks. Because of the newness of the topic, there has been no synthesized summary of the acceptance of the emerging delivery modes, although the importance of the topic has increased with the growth of home deliveries. To fill the knowledge gap, this research systematically reviewed the literature on the willingness to accept drone and robot deliveries using the two largest publication databases: Web of Science and SCOPUS. A total of 46 academic studies were reviewed with respect to their trends, study scope (i.e., type of mode, type of products, modeling framework, and background theories), and factors that positively and negatively affect the willingness. Based on the review, knowledge gaps and the corresponding future research directions were derived: (a) robot-related investigations have been understudied compared to drones; (b) research from the shipper perspective is necessary; (c) transportation and logistics planning-related factors (e.g., socio-economic factors, trip and shipment characteristics) should be investigated; (d) an investigation of users’ behaviors based on actual usage (rather than relying solely on hypothetical scenarios) is necessary; (e) regulatory aspects should be taken into account; and (f) the heterogeneity of products needs to be taken into consideration.

Literature Synthesis of Emerging Last-Mile Delivery Technologies and their Applications to Rural Areas: Drones, Autonomous Delivery Vehicles, and Truck-Drones

Rural areas have the distinct opportunity to become trendsetters of innovation and technology, molding and optimizing delivery advances to operate in a way that meets their needs. Drones, autonomous delivery vehicles (ADVs), and truck-drones have the potential to improve rural delivery services significantly. However, rural environments have considerably different characteristics than urban or suburban areas. Therefore, delivery services must be evaluated specifically for the rural use case because the outcome of rural drone delivery is likely different from urban. This study conducted a systematic literature review about the current state-of-the-art drone, ADV, and truck-drone package delivery in rural areas (excluding medical or healthcare delivery). Drones can significantly reduce rural delivery emissions and costs while increasing efficiency. ADVs have the potential to greatly improve rural delivery efficiency. The truck-drone solution is one of the best mode choices for rural delivery because the truck can travel longer distances while the drone can cross challenging geography without delay. The literature review identified a general need for more drone, ADV, and truck-drone delivery research focusing on rural locations. There also is a need for research about the specific economic, environmental, and societal impacts of drone, ADV, and truck-drone delivery in rural areas. There is a significant gap in the literature on realistic rural delivery modeling and gaps about attitudes and perceptions of drone, ADV, and truck-drone delivery services in rural areas. With additional research, innovative delivery modes and technologies can become more cost-effective, accessible, and efficient in rural areas.

Research on the Optimization Strategy of Last-Mile Distribution under the E-Commerce Logistics Model

With the rapid development of e-commerce, last-mile delivery, as a key link in e-commerce logistics, is essential to provide efficient and punctual delivery services. This study aims to explore the optimization strategy of last-mile delivery under the e-commerce logistics model to improve delivery efficiency, reduce costs, and provide a better user experience. This study adopts the method of literature review and case analysis, combined with the actual e-commerce logistics operation, to conduct an in-depth study on the problem of last-mile delivery.

Optimizing Last Mile Delivery Operations: A Comprehensive Case Study on Flipkart’s Innovative Approach

Effective last-mile delivery operations are essential for both customer happiness and long-term business growth in the ever-changing world of e-commerce. This study thoroughly examines the ground-breaking tactics and creative solutions that Flipkart, one of the biggest e-commerce companies in India, used to streamline its last-mile delivery processes. After a thorough examination that takes into account strategic network development, customer-centric efforts, and technical advancements, this paper clarifies the various tactics that have helped Flipkart become a leader in last mile delivery excellence. This paper examines the larger implications and practical insights for transforming last mile delivery operations in the e-commerce business, based on the analysis of Flipkart's case study. Keywords: Flipkart, supply chain management, e-commerce, last-mile delivery, and logistics optimization.

Optimization of hybrid delivery by vehicle and drones

In this paper, we introduce the optimization of hybrid delivery by vehicle and drones. Hybrid delivery by vehicle and drones is advantageous for improving O2O last-mile delivery efficiency. However, vehicle stop selection and drone delivery sortie arrangement are challenging in the optimization of hybrid delivery by vehicle and drones because cyclic sorties and forward sorties jointly influence the total makespan of the delivery. To minimize the delivery makespan, an MILP model for hybrid delivery is formulated considering both the cyclic sorties and forward sorties of drones. In the proposed model, the intertwined influences of the flight times of cyclic and forward sorties and their further effects on total delivery makespan are depicted. Additionally, we introduce an ACO based on set covering for the selection of vehicle stops and a customized HGSADC for the arrangement of drone sorties. A study based on a simulated case and experiments based on 40 generated instances at different scales are explored to assess the optimization of hybrid delivery by vehicle and drones.

Technical and economic modelling of last-mile transport: A case for Brazil

In response to the escalating demands of urban logistics and the environmental impacts of last-mile deliveries in cities, this study assesses the transition to electric vehicles (EV) in the last-mile delivery transportation sector. We developed a methodology to project last-mile fleets and assess whether electrification considering a scrappage policy makeseconomicsense. This method utilizes socio-economic, geographic, and technical data to assess annual delivery volumes, travel distances, total ownership costs, and breakeven analysis for diesel and electric vehicles, focusing on Brazilian urban centers. Results show that in 2030, in all urban densities, EV have lower operating costs, and they are the more economical choice for all cities or lifespans by 2035. EVs stand out, particularly with extended vehicle lifespans and increased delivery frequencies. Our findings provide a versatile method for assessing the technical and economic feasibility of electric vehicles across diverse demographic areas.

Assessing the expectations of Generation Z customers towards last-mile delivery in E-commerce: A case study in Ho Chi Minh City

This study focuses on assessing the impact of various factors influencing Generation Z consumers' expectations of last-mile delivery services when purchasing goods on e-commerce platforms within Ho Chi Minh City (HCMC), to improve service quality and propose delivery processes for efficient last-mile delivery. What is new compared to previous studies is the emphasis on the impact of environmental protection policies and green initiatives on the expectations of Gen Z customers. In this study, the authors propose the factor "Environmental Protection Policy" to build a scale to measure customer expectations in last-mile delivery service. A survey involving 435 participants who belong to Gen Z and frequently utilize e-commerce services in HCMC provided the primary data for this analysis. Utilizing quantitative analytical techniques, including Cronbach's alpha reliability test, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and multiple regression analysis, this research tested several hypotheses. The results corroborate that the expectations of Gen Z consumers regarding delivery services on e-commerce platforms in HCMC are significantly shaped by five pivotal factors: Delivery speed, reliability, responsiveness, environmental protection policy, and cost. The study notably highlights cost as the predominant factor exerting the most substantial influence on the expectations concerning last-mile delivery services. This study has made a significant contribution to the body of knowledge that e-commerce platforms and logistics firms may use to raise the bar for delivery services that Gen Z consumers anticipate.

UAV-Based Delivery Systems: A Systematic Review, Current Trends, and Research Challenges

The rising popularity of drones significantly impacts package delivery services, offering both unique opportunities and challenges. This survey explores the diverse applications of drones for last-mile deliveries, highlighting their capacity to access remote areas and create new business prospects. Use cases, ranging from critical medical deliveries to addressing COVID-19 pandemic needs, underscore the transformative potential of drone technology. While recognizing drones’ eco-friendly attributes in eliminating harmful gas emissions, the survey addresses battery constraints, necessitating an investigation into physical energy models to extend flight autonomy. This becomes crucial for operational capabilities, especially in adverse weather conditions. A reliable communication infrastructure is crucial for the success of drone operations in package delivery, especially during unexpected events, as seamless connectivity plays a key role in facilitating efficient control and monitoring between ground stations and drones. This enables dynamic rerouting, enhancing overall delivery reliability. The survey explores innovative approaches, including collaborations with other vehicles like trucks, trains, and buses, optimizing the last-mile delivery process. Despite the transformative potential, concerns about privacy, security, safety, and risk management in drone delivery are acknowledged. The work also emphasizes responsible and ethical implementation, considering diverse concerns associated with widespread adoption. In contrast to existing survey articles focused on specific technical aspects, this comprehensive survey broadens its scope. It covers ethical issues, sustainability aspects, healthcare systems, physics models, innovative approaches, reliable communications, security and safety concerns, and real test-beds in drone-based delivery systems. The survey not only identifies potential applications and tackles technical challenges but also integrates broader considerations. In addition, this work extensively explores the motivations, lessons learned, and future directions in the realm of drone delivery. Analyzing existing literature, it provides valuable insights for researchers, industry professionals, policymakers, and stakeholders keen on understanding the dynamic evolution of drone technology in the package delivery domain.

DELIVERY AUTOMATION ROBOT USING ARDUINO MICROCONTROLLER

The Delivery Automation Robot project aims to develop a robust and efficient autonomous delivery robot for last-mile logistics operations. Built upon a foundation of sturdy hardware components including a four-wheel metal chassis and large wheels, the Delivery Automation Robot ensures stability and durability while navigating diverse terrains. Integrated with advanced control systems such as the L298n motor driver shield, NODEMCU, and Arduino Uno, the robot offers precise movement control and data processing capabilities. Equipped with essential sensors like the magnetometer HMC5883 and NEO 6m GPS module, the MDAR achieves accurate localization and navigation, crucial for optimizing delivery routes. Additionally, wireless communication facilitated by the HC06 Bluetooth module enables remote monitoring and control. Overall, the Delivery Automation Robot represents an innovative solution poised to revolutionize last-mile delivery processes, enhancing efficiency and reliability in logistics operations. Keywords: four-wheel chassis, L298n motor driver, NODEMCU, Arduino Uno, magnetometer HMC5883, NEO 6m GPS module, HC06 Bluetooth module.

SmallMap: Low-cost Community Road Map Sensing with Uncertain Delivery Behavior

Accurate road networks play a crucial role in modern mobile applications such as navigation and last-mile delivery. Most existing studies primarily focus on generating road networks in open areas like main roads and avenues, but little attention has been given to the generation of community road networks in closed areas such as residential areas, which becomes more and more significant due to the growing demand for door-to-door services such as food delivery. This lack of research is primarily attributed to challenges related to sensing data availability and quality. In this paper, we design a novel framework called SmallMap that leverages ubiquitous multi-modal sensing data from last-mile delivery to automatically generate community road networks with low costs. Our SmallMap consists of two key modules: (1) a Trajectory of Interest Detection module enhanced by exploiting multi-modal sensing data collected from the delivery process; and (2) a Dual Spatio-temporal Generative Adversarial Network module that incorporates Trajectory of Interest by unsupervised road network adaptation to generate road networks automatically. To evaluate the effectiveness of SmallMap, we utilize a two-month dataset from one of the largest logistics companies in China. The extensive evaluation results demonstrate that our framework significantly outperforms state-of-the-art baselines, achieving a precision of 90.5%, a recall of 87.5%, and an F1-score of 88.9%, respectively. Moreover, we conduct three case studies in Beijing City for courier workload estimation, Estimated Time of Arrival (ETA) in last-mile delivery, and fine-grained order assignment.

Performance estimation and operating policies in a truck-based autonomous mobile robot delivery system

Last-mile delivery is a costly and time-consuming process in e-commerce operations. Piloted by several companies, autonomous mobile robots cooperating with trucks have been implemented for parcel delivery. In this system, a truck departs from the warehouse, carrying robots and parcels, and traverses several drop-off points to release robots for parcel delivery or to deliver parcels by itself. We focus on performance estimation and system configuration, considering the no-zoning policy, where all trucks serve the whole delivery area and the zoning policy, where each truck takes charge of one zone. A queuing network is constructed to estimate the parcel throughput time and a cost minimisation model is developed for the system with a required throughput time. The optimal number of drop-off points and batch size can be numerically found to minimise the order throughput time. The zoning policy is cheaper than no-zoning policy for a small number of drop-off points and a short required throughput time, and it is cheaper in a system with a large number of drop-off points. Moreover, we find that while the truck-based autonomous mobile robot delivery system typically has a larger order throughput time than a delivery system using only robots, it is much less costly.

Multi-period heterogeneous fleet vehicle routing problem with self-pickup point selection: a last-mile delivery scenario in urban and rural areas

Multi-period heterogeneous fleet vehicle routing problem with self-pickup point selection: a last-mile delivery scenario in urban and rural areas

Optimizing Last-Mile Delivery: A Multi-Criteria Approach with Automated Smart Lockers, Capillary Distribution and Crowdshipping

Background: This publication presents a review, multiple criteria optimization models, and a practical example pertaining to the integration of automated smart locker systems, capillary distribution networks, crowdshipping, last-mile delivery and supply chain management. This publication addresses challenges in logistics and transportation, aiming to enhance efficiency, reduce costs and improve customer satisfaction. This study integrates automated smart locker systems, capillary distribution networks, crowdshipping, last-mile delivery and supply chain management. Methods: A review of the existing literature synthesizes key concepts, such as facility location problems, vehicle routing problems and the mathematical programming approach, to optimize supply chain operations. Conceptual optimization models are formulated to solve the complex decision-making process involved in last-mile delivery, considering multiple objectives, including cost minimization, delivery time optimization, service level minimization, capacity optimization, vehicle minimization and resource utilization. Results: The multiple criteria approaches combine the vehicle routing problem and facility location problem, demonstrating the practical applicability of the proposed methodology in a real-world case study within a logistics company. Conclusions: The execution of multi-criteria models optimizes automated smart locker deployment, capillary distribution design, crowdshipping and last-mile delivery strategies, showcasing its effectiveness in the logistics sector.