The last-mile delivery option has become a focal point of academic research and industrial development in recent years. Multiple factors such as increased demands on delivery flexibility, customer requirements, delivery urgency, and many others are enforcing to adopt this option. For fulfilling this paradigm shift in delivery and providing additional flexibility, drones can be considered as a viable option to use for last-mile delivery cases. Numerous drones are available in the market with varying capacities and functionalities, posing a significant challenge for decision-makers to select the most appropriate drone type for a specific application. For this purpose, this study proposes a comprehensive list of criteria that can be used to compare a set of available last-mile delivery drones. Additionally, we introduced a systematic multi-criterion, multi-personnel decision-making approach, referred to as the Interval Valued Inferential Fuzzy TOPSIS method. This method is robust and can handle the fuzziness in decision-making, thereby providing quality drone selection decisions under different applications. We then apply this method to a real-life test setting. Results suggest that smaller drones or quadcopters are considered viable to use in urban environments, while long-range drones are preferred for the last mile delivery needs in rural settings.

Bakgrund. E-handel ökar ständigt, och med det även frakt av ehandelsvaror. Frakten som skrivs om i den här studien syftar till den frakt som sker mellan en återförsäljare och en slutkonsument. Denna är i texten kallad last-mile delivery. Denna är identifierad som mycket kostnadsbärande för återförsäljare och därför har ansträngningar gjorts för att ta reda på vad som driver konsumentpreferenser vid frakt av ehandelsvaror. För att bredda det här fältet och den nuvarande kunskapen inom område har den här studien introducerat tidspreferensteori som underlag och adderat betalningsfördröjning som attribut vid last-mile delivery för att se vilken effekt detta har på preferenser vid fraktval. Syfte. Syftet med den här studien är att ta reda på hur en fördröjd betalning kan påverka preferenserna för olika last-mile delivery-alternativ. Överlag syftar också studien till att bredda kunskapen inom området. Detta görs alltså med introduktionen av tidspreferensteori till området. Metod. Studien är en experimentstudie med en ansluten enkät. Enkäten gjordes i tre utföranden och skickades ut i tre distinkta experimentgrupper. Därefter testades datan med ett icke-parametriskt proportionstest för att se om det fanns någon signifikant mängd svar som stödjer att en fördröjd betalning påverkar konsumentens val av last-mile delivery-alternativ. Resultat. Resultaten av studien visar att det inte finns någon koppling mellan en fördröjd betalning och ändrade konsumentbeteenden i fraktpreferenser. Överlag så valdes fraktalternativet med lägst frakt. Detta är något som går igen i flera tidigare studier där man kommit fram till att fraktkostnad och leveranshastighet är de två mest betydelsefulla aspekterna av frakten. Det enda scenariot som visade någon förändring i preferens var då produkten vid köpet var en dyr sådan. Huruvida preferensskiftet går att tillskriva den fördröjda betalningen förblir oklart, men inte osannolikt. Slutsatser. Slutsatsen till studien blir att trots tidspreferens och fördröjd betalning användes i studien så gav de inget mervärde. Resultatet blev i linje med tidigare resultat. Att tidspreferensteorin inte höll för fraktpreferenserna kan haft att göra med studiedesignen. En framtida studie hade kunnat göra ett mer ingående arbete och fokusera ännu mer på tidspreferensen för att hitta nya resultat / Background. E-commerce is ever expanding, and with it, so is last-mile delivery. Last-mile delivery is the last part of any delivery from a retailer or etailer (online retailer) to a consumer. Last-mile delivery is one of the most costly parts of the supply chain for many etailers and as such efforts have been made to understand what drives preferences for last-mile delivery. To broaden this field, this study will introduce time preference theory to the last-mile delivery and examine if delayed payment of an online purchase has any effect on the last-mile deliver preferences.  Objectives. The objectives of this study are to examine if delayed payment of online purchases has any effect on the last-mile delivery preference for consumers, as well as broaden the knowledge on last-mile delivery preferences in general. This is done with the inclusion of time preference theory as an underlying theory.  Methods. The study is carried out through the use of an experiment study with an experiment survey. The survey was made into three different versions, distributed to three different experiment groups. The data was then tested with a non-parametric proportion test with varying values of proportion to see whether there was any significant proportion of the replies that were in favor of delay of payment having any effect on the consumer preference.   Results. The results of the study showed that consumers generally choose the last-mile delivery option with the lowest delivery fee. This is in line with previous findings which concluded that delivery fee and delivery speed are the two most important factors for consumers. The only case in which consumers indicated that there was any effect of the payment delay was in the case of an expensive product. Even then it is hard to rule out that it was not something else that brought this result.   Conclusions. The concluding findings of the study is that while time preference was added as an attribute for last-mile delivery, it had little to no effect. This may have been because of the study design of this study. For future research on the topic, examining time preference in a greater depth may give different findings from this study.

Background: The strong growth of e-commerce and the connected last mile delivery problems as well as the increasing customer demands have driven forward delivery innovations in the past years. One of them, parcel locker networks, were developed and have been growing for several years. However, customers still seem to prefer the traditional home delivery, which is highly inefficient for last mile delivery actors. Thereby, it has to be evaluated whether customers are satisfied with the parcel locker technology and which factors determine the satisfaction.  Purpose: This study aims at evaluating the factors influencing customer satisfaction in regard to parcel lockers. Therefore, relevant constructs about satisfaction and acceptance models in the last mile context were derived from the literature. Method: In order to accomplish our purpose, a quantitative study was conducted using a questionnaire among end customers in Austria and Germany. The proposed framework and hypotheses were analysed by using structural equation modelling. Furthermore, a multigroup analysis was conducted to identify differences between sociodemographic categories.  Conclusion: The results show that perceived ease of use, perceived quality and convenience perception all have an influence on customer satisfaction in Germany and Austria. However, the direct influence of perceived ease of use and convenience perception cannot be confirmed, both constructs are entirely mediated by perceived quality. Furthermore, the multigroup analysis determined significant differences in the gender category for the path between perceived ease of use and convenience perception, in the living area category for the relationship between convenience perception and perceived quality and in the age category for perceived quality and customer satisfaction.

When a package is shipped, the customer often requires the delivery to be made within a particular time window or by a deadline. However, meeting such time requirements is difficult, and delivery companies may not always know ahead of time which customers will need a delivery. In this thesis, we present models and solution approaches for two stochastic last-mile delivery problems in which customers have delivery time constraints and customer presence is known in advance only according to a probability distribution. Our solutions can help reduce the operational costs of delivery while improving customer service. The first problem is the probabilistic traveling salesman problem with time windows (PTSPTW). In the PTSPTW, customers have both a time window and a probability of needing a delivery on any given day. The objective is to find a pre-planned route with an expected minimum cost. We present computational results that characterize the PTSPTW solutions. We provide insights for practitioners on when solving the PTSPTW is beneficial compared to solving the deterministic analogue of the problem. The second problem is the same-day delivery problem (SDDP). The SDDP is a dynamic and stochastic pick-up and delivery problem. In the SDDP, customers make delivery requests throughout the day and vehicles are dispatched from a warehouse or brick and mortar store to serve the requests. Associated with each request is a request deadline or time window. In order to make better-informed decisions, our solution approach incorporates information about future requests into routing decisions by using a sample scenario planning approach with a consensus function. We also introduce an analytical result that identifies when it is beneficial for vehicles to wait at the depot. We present a wide range of computational experiments that demonstrate the value of our approaches.

E-commerce has been growing in Sweden over the years. It has not only contributed to economy, but also has shaped people’s way of living, especially with the service of home delivery. Consumers enjoy the various choices of products with reasonable prices and the convenience of receiving parcels with a single click on the mouse or by using their phones. Meanwhile, the problem of not-at-home and repeated delivery have caused trouble for both consumers and logistic service providers leading to an increase in delivery cost. Therefore, it takes a lot of cooperation and innovations to come up with solution which will both convenient to customer and 3PL providers, which we call ‘last mile delivery’.This thesis was written with purpose of evaluating the solutions used to address the not at home problem of last mile in e-Commerce. Moreover, the thesis seeks find out which of these solutions are preferred by customers and the impact of these solution on customers. The thesis focuses on the Swedish customers because they have more experience buying online.In this thesis we first established a literature review of E-commerce, E- Shoppers preference of last mile delivery, last mile delivery concept, last mile logistics solution (not at home) which we came up with a theoretical framework by examining the impact of last mile delivery. In order to answer the research questions a focus group discussion and nine interviews were carried out focusing mainly on professional and non professional customers in Sweden. The study identified that apart from home delivery, the customers in Sweden mainly use Collection Points in online shopping. Some other delivery methods such as automated locker banks and controlled home access exist but still in early stage. After analyzing the literature review, current solutions and empirical findings, the study concluded with three potential solutions to solve not at home problem. These solutions are - Secured room at residential building to drop parcel, Automated Locker Bank and Collection Points more closer to residential area.

Background: E-commerce has experienced tremendous growth in the past few years. At the same time, the Covid-19 pandemic has swept across the world. As a result, many people became enforced to stay more at home because of restrictions and lockdowns, resulting in an even larger increase for the e-commerce industry, and some changes in consumer behavior. In relation to this, the last-mile delivery industry has seen demand shock as a result of the increased volumes within e-commerce. Purpose: The purpose of this paper aims to answer two research questions: How have Swedish e-consumer behaviors and preferences towards delivery services changed due to the Covid-19 pandemic? And how will Swedish e-consumer behaviors and preferences towards delivery services change after the Covid-19 pandemic? Method: With the research questions in mind, an exploratory inductive study was developed using qualitative and quantitative data. As a result, an interview and a survey were developed. The interview provided first-handed insights from the industry to better give an understanding of the challenges of the pandemic and the effect on consumer preferences. The survey on the other hand investigated consumer preferences regarding five different LMD service offerings: home delivery iiwithout signature, home delivery with signature, delivery to service points, delivery to parcel lockers, and pick-up at web shop's physical store. Another aspect of the survey is that the consumer preference is explored before, during, and after the pandemic.  Conclusion: The findings of this study conclude that Covid-19 has significantly impacted peoples' preferences regarding last-mile delivery preferences. As a general conclusion, consumers prefer delivery methods which reduce human contact as well as travel distance. The findings of this study will provide the industry with meaningful insights as well as contributing to the existing knowledge of last-mile delivery.

Abstract Purpose: The purpose of this study is to explore last mile delivery practices among large and medium Swedish omni-channel (OC) retailers and e-tailers. Also, the study aims at analyzing what similarities and differences exist between the two types of retailers. Method: A literature review was carried out in order to gain more knowledge about the topic and develop a theoretical framework, used for analyzing data. Also, a quantitative study was conducted through electronic surveys (secondary data) and website observations (primary data). The 100 retailers were large and medium OC retailers and e-tailers and were selected based on a probability sample.  Findings: The study has shown that there are plenty of similarities and differences between the two kinds of retailers. Some of the delivery practices and options that OC retailers and e-tailers perform similarly are unattended HD (unattended home delivery), attached C&C (click and collect), drop shipping, free solitary C&C (click and collect). There are also differences between retailers when it comes to attended HD, time slot, eco delivery or LTL-Courier (Less Than Truckload-courier). E-tailers offer more competitive remote deliveries with more free remote delivery options. OC retailers leverage on both store network and remote delivery services. Thus, OC retailers can learn how to cope with e-commerce growth and adapt their delivery services as e-tailers do. Limitations: This study has a geographical focus on Swedish OC retailers and e-tailers. The data that was collected has been limited to the logistics variables: delivery mode, velocity, time slot, slot price differentiation, delivery fee, eco delivery, picking location, delivery area and transport service. Theoretical implications: This study is an important step towards contributing to academic theoretical literature regarding last mile delivery practices. Based on the previous frameworks, new logistical variables were added, such as more velocities, delivery fee, eco delivery and drop shipping. These contributions were helpful in the process of exploring characteristics about retailers and how they differ from each other. Managerial implications: This research is valuable for managers and retailers in order to find the best logistical strategy. It could be beneficial for OC retailers who face challenges that e-commerce brings and compete with e-tailers. Keywords: Last-mile delivery, Retailing, Omni-channel, E-tailers, E-commerce. Paper type: Research paper

<p>  </p> <p>Hydrogen fuel cells are an abundant and cleaner source of energy, making them an attractive option for powering transportation systems. Hydrogen fuel cell drones are a new type of drone that generates energy from fuel cells for flight and expels heat and water vapor as byproducts. Compared to battery-powered drones, hydrogen fuel cell drones have better endurance and payload capacity due to their higher energy density, making them more efficient for eCommerce delivery. This research compares the performance of hydrogen and battery delivery drones for both drone-only and truck-drone last-mile delivery systems. A mixed integer programming model has been formulated to minimize the total delivery time for small to medium customer instances using the two-echelon vehicle routing problem, where drones are launched from the truck to serve one or more customers. The study conducted a comparative analysis by varying different parameters of drones on multiple sets of customer instances from real-world data to determine the best choice of drones for different scenarios. The results of the analysis show that hydrogen fuel cell drones have significant delivery advantages over typical battery drones in terms of delivery time and efficiency. Additionally, a sensitivity analysis was conducted to demonstrate the impacts of different parameters on the objective function of the delivery systems.</p>

Missed deliveries are a major issue for package carriers and a source of great hassle for the customers. Either the carrier attempts to redeliver the package, incurring the additional expense of visiting the same house up to three times, or they leave the package on the doorstep, vulnerable to package thieves. In this dissertation, a system of collection-and-delivery-points (CDPs) has been proposed to improve customer service and reduce carrier costs. A CDP is a place, either in an existing business or a new location, where the carrier drops any missed deliveries and the customers can pick the packages at their convenience. To examine the viability of a CDP system in North America, a variation on a location-routing problem (LRP) was created, a mixed-integer programming model called the CDP-LRP. Unlike standard LRPs, the CDP-LRP takes into account both the delivery truck route distance and the direct customer travel to the CDPs. Also, the facilities being placed are not located at the beginning and ending of the truck routes, but are stops along the routes. After testing, it became clear that, because of the size and complexity of the problem, the CDP-LRP is unable to be solved exactly in a reasonable amount of time. Heuristics developed for the standard LRP cannot be applied to the CDP-LRP because of the differences between the models. Therefore, three heuristics were created to approximate the solution to the CDP-LRP, each with two different embedded modified vehicle routing problem (VRP) algorithms, the Clark-Wright and the Sweep, modified to handle the additional restrictions caused by the CDPs. The first is an improvement heuristic, in which each closed CDP is tested as a replacement for each open CDP, and the move that creates the most savings is implemented. The second begins with every CDP open, and closes them one at a time, while the third does the reverse and begins will only one open CDP, then opens the others one by one. In each case, a penalty is applied if the customer travel distance is too long. Each heuristic was tested for each possible number of open CDPs, and the least expensive was chosen as the best solution. Each heuristic and VRP algorithm combination was tested using three delivery failure rates and different data sets: three small data sets pulled from VRP literature, and randomly generated clustered and uniformly distributed data sets with three different numbers of customers. OpenAll and OpenOne produced better solutions than Replacement in most instances, and the Sweep Algorithm outperformed the Clark-Wright in both solution quality and time in almost every test. To judge the quality of the heuristic solutions, the results were compared to the results of a simple locate-first, route-second sequential algorithm that represents the way the decision would commonly be made in industry today. The CDPs were located using a simple facility location model, then the delivery routes were created with the Sweep algorithm. These results were mixed: for the uniformly distributed data sets, if the customer travel penalty threshold and customer density are low enough, the heuristics outperform the sequential algorithm. For the clustered data sets, the sequential algorithm produces solutions as good as or slightly better than the sequential algorithm, because the location of the potential CDP inside the clusters means that the penalty has less impact, and the addition of more open CDPs has less effect on the delivery route distances. The heuristic solutions were also compared to a second value – the route costs incurred by the carrier in the current system of redeliveries, calculated by placing additional customers in the routes and running the Sweep algorithm – to judge the potential savings that could be realized by implementing a CDP system in North America. Though in some circumstances the current system is less expensive, depending on the geographic distribution of the customers and the delivery failure rate, in other circumstances the cost savings to the carrier could be as high as 27.1%. Though the decision of whether or not to set up a CDP system in an area would need to be made on a case-by-case basis, the results of this study suggest that such a system could be successful in North America. / Doctor of Philosophy / Missed deliveries are a major issue for package carriers and a source of great hassle for the customers. Either the carrier attempts to redeliver the package, incurring the additional expense of visiting the same house up to three times, or they leave the package on the doorstep, vulnerable to package thieves. In this dissertation, a system of collection-and-delivery-points (CDPs) has been proposed to improve customer service and reduce carrier costs. A CDP is a place, either in an existing business or a new location, where the carrier drops any missed deliveries and the customers can pick the packages at their convenience. To examine the viability of a CDP system in North America, a mathematical programming model was created called the CDP-LRP. Because of the size and complexity of the problem, it is unable to be solved exactly in a reasonable amount of time. Therefore, three heuristics were created to approximate the solution to the CDP-LRP, each with two different embedded modified vehicle routing problem (VRP) algorithms. For all the heuristics, a penalty is applied if the customer travel distance is too long. Each heuristic and VRP algorithm combination was tested using different data sets: three small data sets pulled from VRP literature, and randomly generated clustered and uniformly distributed data sets with three different numbers of customers. To judge the quality of the heuristic solutions, the results were compared to the results of a simple locate-first, route-second sequential algorithm that represents the way the decision would commonly be made in industry today. These results were mixed: for the uniformly distributed data sets, if the customer travel penalty threshold and customer density are low enough, the heuristics outperform the sequential algorithm. For the clustered data sets, the sequential algorithm produces solutions as good as or slightly better than the sequential algorithm, because the location of the potential CDP inside the clusters means that the penalty has less impact, and the addition of more open CDPs has less effect on the delivery route distances. The heuristic solutions were also compared to a second value – the route costs incurred by the carrier in the current system of redeliveries – to judge the potential savings that could be realized by implementing a CDP system in North America. Though in some circumstances the current system is less expensive, depending on the geographic distribution of the customers and the delivery failure rate, in other circumstances the cost savings to the carrier could be as high as 27.1%. Though the decision of whether or not to set up a CDP system in an area would need to be made on a case-by-case basis, the results of this study suggest that such a system could be successful in North America.

This thesis deals with light utility vehicle design (class N1). Apart from designing vehicle’s appearance, other goals such as finding suitable usage of this electric vehicle type or adapting design to user’s needs and new technologies available were set. Usage of light e-van as a last mile delivery vehicle is proposed and following design process takes this purpose into account. Reasoning behind determining decisions is also given in this thesis. Final design stands out with original shaping, while possibilities of colour and graphics make it easily distinguishable among other vehicles. Design also suggests multiple changes in ergonomics of the vehicle, focused mainly on driver’s comfort and overall adaptation to selected vehicle’s use.