Parcel Delivery Service Research Articles

Protecting Digital Society: Policies for Criminalizing Illegal Smartphone Applications Through Cyber Law Frameworks

This research aims to contribute to the development of criminal law policies addressing the widespread distribution of smartphone applications, both APK and iOS, that are used as tools for unauthorized online loan activities, online fraud, threats, and intimidation. These applications often disguise themselves as legitimate online loan platforms, wedding invitation apps, and parcel delivery services. Upon download, they illicitly debit mobile banking accounts or present themselves as government auction platforms for criminal goods at discounted prices, posing significant threats to consumers, debtors, and the general public. Theoretical framework: The foundation of this research lies in cyber law theory, which endeavors to create legal strategies to address cybercrimes and safeguard the digital community. This study utilizes a multidisciplinary approach, integrating legal analysis, policy assessment, and collaboration with stakeholders. Methods: This study utilized the normative juridical method to examine digital policies by criminalizing illegal smartphone applications through cyber law policies. This approach involves a systematic legal analysis of current regulations, assessing their effectiveness, and suggesting formal legal measures to address new threats posed by unauthorized applications, with an emphasis on protecting digital society from harm. Results and Conclusions: This indicates a pressing need for comprehensive criminal law policies specifically designed to effectively combat these unauthorized applications. Such policies are crucial in preventing and mitigating the harms caused by these applications before they impact society. The author's contribution lies in proposing formal offenses against the creators and disseminators of these applications. malicious applications, thereby bridging the current gap in legal measures to counteract digital criminal activities. Originality/Value: This research underscores the urgency of formulating and implementing cyber law policies to safeguard the public from the detrimental effects of illicit smartphone applications. Its originality lies in proposing innovative legal strategies to proactively address emerging digital threats.

Auction-Based Crowdsourced First and Last Mile Logistics

The booming of mobile internet and crowdsourcing technology has offered great opportunities for first and last mile logistics (FLML) service. Unlike the traditional FLML service that separates the parcel collection in the first mile from the parcel delivery in the last mile, a new type of crowdsourced FLML service integrates parcel collection and parcel delivery services as a whole, which can significantly improve the efficiency of FLML service. Briefly, in a crowdsourced FLML service, the platform assigns the customers' triggered pick-up parcels to the couriers who are delivering drop-off parcels in terms of the real-time status of couriers ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> , capacity, location, and schedule). Existing works solving the crowdsourced FLML problem only consider the utility maximization for the platform but ignore the incentive to the utilities of couriers. Inspired by this, in this paper, we investigate a novel type of crowdsourced FLML problem, namely <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Auction-based Crowdsourced FLML (ACF)</i> , where the platform assigns the couriers with suitable pick-up parcels based on the preferences of couriers with the goal of maximizing the social welfare of the platform and couriers. To solve the ACF problem, we present a novel auction model named <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Multi-attribute Reverse Vickrey (MRV)</i> , where the couriers bid on parcels according to their preferences for parcels. Based on the MRV model, we present three efficient assignment algorithms to assign parcels to couriers. In addition, we give theoretical analysis for our proposed algorithms. Extensive experiments examine the efficiency and effectiveness of our solutions.

Effects of Parcel Delivery Service on Customer Satisfaction in the Saudi Arabian Logistics Industry: Does the National Culture Make a Difference?

Background: The logistics industry is keen to meet customer expectations, which in turn supports trade by enhancing business competitiveness and promoting economic development. Logistics companies realized that fulfillment of customer needs has a significant effect on their business survival, their sales and ultimately their profits. This research analyzes the variables that influence customer satisfaction with parcel delivery services in the Kingdom of Saudi Arabia (KSA), particularly the SERVQUAL dimensions: tangibility, reliability, responsiveness, assurance, and empathy. The research also examined whether national culture affects customer perceptions of parcel delivery services in KSA or not. Methods: The research collected data using a self-administered survey, which was directed at a sample of customers in the KSA, who had recent experience with parcel delivery services. Results: The results of statistical analysis showed that the best predicators of customer satisfaction are reliability, followed by the dimensions of empathy, then tangibility and finally responsiveness. In addition, the results showed significant differences in customers’ overall satisfaction between Saudis and non-Saudis. Saudis were more satisfied with the service than non-Saudis were. Conclusions: This research showed the key role of national culture in perceiving parcel delivery service quality in KSA. The findings provide important messages to the administrators of the logistics services in KSA, which have become crucial for the Saudi Vision 2030. They need to customize their service according to customer needs and provide regular training for their staff to be supportive, reliable and have the credibility to deliver services as promised.

Human-Centric Parcel Delivery at Deutsche Post with Operations Research and Machine Learning

Features such as estimated delivery time windows and live tracking of shipments play a key role in improving the customer experience in last-mile delivery. The building blocks for enabling these features are reliable knowledge about the expected order of deliveries in a tour and precise delivery time window predictions. For Deutsche Post’s parcel delivery service in Germany, we developed a courier-centric routing algorithm and a corresponding state-of-the-art machine learning model for delivery time window predictions. The routing algorithm combines operations research with statistics and machine learning to implicitly gather and use the tacit knowledge of our experienced couriers within the tour generation. This is achieved by deducing and selecting appropriate precedence constraints from historical delivery data. This novel combination of optimization with data-driven constraints enabled us to provide custom routes to the individual couriers. It proved to be a main driver allowing us to provide accurate delivery time window predictions and live tracking of shipments. Our solution is used by Deutsche Post to plan the daily routes of couriers to the approximately 13,000 parcel delivery districts in Germany as well as to provide live tracking and estimated delivery time windows for 1.6 million parcels each day. History: This paper has been accepted for the INFORMS Journal on Applied Analytics Special Issue—2022 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research.

Sustainability Aspects of Drone-Assisted Last-Mile Delivery Systems—A Discrete Event Simulation Approach

The goal of this article is to examine the advantages and disadvantages of the application of drones in last-mile delivery systems from a sustainability point of view regarding CO2 emissions and energy consumption. As commercial drones are developing rapidly, the application of such tools in the field of last-mile delivery and transportation can offer many opportunities to increase service flexibility, reduce delivery time and decrease CO2 emissions and energy consumption. In this article, a discrete event simulation is applied to examine how the assistance of drones in parcel delivery services can influence the sustainability aspects of such services regarding CO2 emissions and energy consumption in an urban environment. Based on factory parameters, a vehicle-based delivery scenario is compared to a drone-assisted scenario under ideal conditions. According to the results, within the simulation parameters with the assistance of drones, a decrease in CO2 emissions and energy consumption is possible in last-mile delivery services, but more environmental, technological and financial limitations should also be addressed and incorporated to determine whether such a development is worthwhile from a last-mile delivery company’s point of view.

Evaluation of community science monitoring with environmental DNA for marine fish species: “Fish survey project using environmental DNA”

AbstractEnvironmental DNA is a powerful tool for community science‐based biodiversity surveys. However, the effectiveness of environmental DNA for environmental education and the time and physical costs perceived by volunteers for collecting environmental DNA remain unclear. Here, we evaluated a community science program for monitoring marine fish biodiversity using environmental DNA metabarcoding. This program aimed to investigate marine fish biodiversity in coastal areas along the Japanese archipelago. The participants were allowed to decide on the date and site to collect environmental DNA. They received a paper manual, a data sheet, and a sampling kit via a parcel delivery service. Before collecting environmental DNA, they watched a video manual for collecting environmental DNA and attended a webinar about the process and precautions for collecting environmental DNA provided by the scientists. At the sampling sites, they obtained environmental DNA samples from seawater themselves and sent the samples to the scientists via a refrigerated parcel delivery service. After collecting environmental DNA, they received fish name data from their samples and attended a webinar about survey results provided by the scientists. A cumulative total of 168 volunteers (84 pairs) participated in the program and detected 572 taxonomic groups of fish environmental DNA in the summer of 2020 and 2021. According to a questionnaire survey, more than 75% of the respondents answered that the project improved their understanding of biodiversity, marine environments, and environmental DNA. Approximately 95% of the respondents thought that environmental DNA collection work was meaningful to them. Some respondents commented on the difficulty of interpreting their fish name data, or the time and effort of selecting a sampling site. Therefore, improving the methods to communicate more information about fish name data and select sampling sites will further develop community science monitoring using environmental DNA.

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.

Strategy for the Siting of Electric Vehicle Charging Stations for Parcel Delivery Service Providers

The development of urban logistics is closely related to the inhabitants of specific areas. People are changing their shopping habits, hence the growing share of online shopping. The consequence of the foregoing is increased demand for parcel delivery to customers’ addresses as well as in-store and automated pick-up points. This has increased the number of couriers that provide parcel delivery services. To achieve sustainable development, there is a real need to convert conventional combustion engine fleets using greener solutions such as electric vehicles. However, introducing such vehicles on a large scale involves constraints such as the vehicle running range on a single charge, the price of a new fleet and of its maintenance, and the location of charging stations. This article focuses on the strategies for siting of charging stations intended to be used by the providers of parcel delivery services. Different strategies as well as a method for identifying optimal goal-specific locations have been proposed. The results show the limitations and challenges facing both the operators of parcel delivery services and local authorities that should also be involved in the development of charging points. Additionally, based on the method presented in the paper, operators can choose between different strategies depending on the particular requirements and local conditions.

Drone noise in my backyard: the challenges for public acceptability

The introduction of drones in urban areas for surveillance, parcel delivery services, air taxis, or other services have raised the issue of public acceptability. How can this concept known as Urban Air Mobility (UAM) be successfully introduced in an area without upsetting communities? And how can not yet known benefits of these services be compared to feared drawbacks? Noise impact is already considered to be one of the main concerns for successful introduction of UAM, but focusing on noise levels exclusively may not be enough. Based on recent research on noise annoyance and how it affects individuals and communities, a holistic approach, including noise impact, as well as non-acoustical factors, is presented to address the annoyance towards these disruptive air vehicles. Subjective measures should be considered including demographic factors, as well as perceptional factors, such as the visual environment where these vehicles operate, and emotional factors such as attitude towards drones and air taxis. Using this approach, studies on noise impact of UAM will be able to evaluate the use cases in their intended setting and with the appropriate target communities to assess the true impact and define the real challenges to overcome for noise research in the coming decade.

Simulation optimization for parcel hub scheduling problem in closed-loop sortation system with shortcuts

With the growth of e-commerce, the quantity of delivery orders and parcels is steadily increasing. Reliable and fast parcel delivery services are of utmost importance to customers. To achieve this target, the central parcel consolidation terminals (CPCT) known as parcel sorting hubs are dedicated to improving the operational efficiency especially in the optimal scheduling of inbound trucks. This study aims to determine the optimal schedule and assignment of inbound trucks to the inbound docks, known as the parcel hub scheduling problem with shortcuts (PHSPwS), for minimizing the expected makespan and expected waiting time of inbound trucks in the closed-loop automated sorting conveyor (ASC) system with shortcuts of the parcel sorting hubs. We first construct a mathematical formulation to present the PHSPwS problem based on the traffic control model. However, due to the congestion behavior on the conveyors and stochastic and dynamic nature of the ASC system, the expected objective functions are not analytically available from the mathematical model. Then, a simulation optimization (SO) approach combined with an adaptive genetic-based discrete particle swarm optimization (AGDPSO) algorithm is proposed to tackle the PHSPwS problem in a stochastic and dynamic ASC environment. The closed-loop ASC simulation model is first established to describe the detail operation of the closed-loop ASC sortation system with shortcut. Based on performance evaluation of this simulation model, a novelty algorithm AGDPSO, which hybridized genetic algorithm and particle swarm optimization algorithm with self-tuning parameters is developed to search and find the optimal inbound truck schedule in the large-scale solution space. In particular, the time-varying acceleration coefficients embedded in the AGDPSO are adopted to amplify the effectiveness of the global and local best solutions to obtain a better balance between exploration and exploitation of the searching space. The experimental results reveal that AGDPSO outperforms other algorithms and provides a better and more stable solution. Moreover, the impact of the strategic and operational factors of the closed-loop ASC system for the expected makespan and truck queueing time are also investigated, while the automatic truck unloading mode is confirmed to significantly improve the system efficiency.

Service quality and timeliness: Empirical evidence on the parcel delivery service in Indonesia

The problems influencing the service quality of Lion Parcel Halim Perdana Kusuma Jakarta were that the delivery time needed to be by the delivery receipt and that there needed to be a complete list. This research aimed to know and analyze the service quality and the direct and indirect influence of delivery cost on customer satisfaction through timeliness. The population used in this research was the customers of Lion Parcel Halim Perdana Kusuma Jakarta, with a sample of as many as 139 respondents. The technique of data analysis used was Structural Equation Modelling with the approach of Partial Least Square. The key finding of this research was that customers considered the service quality of Lion Parcel could be better, making them dissatisfied with the quality of service delivered by Lion Parcel. Whereas the service quality and delivery cost directly influenced, timeliness and timeliness influenced customer satisfaction. It was also found that timeliness indirectly and significantly mediated the influence of service quality and delivery cost on customer satisfaction.

Analysis of Service Efficiency of Parcel Locker in Last-mile Delivery: A Case Study in Norway

The rapid growth of e-commerce is challenging last-mile parcel delivery services. Traditionally, parcel delivery is done using vans which deliver individual parcels to customers’ home (“home deliveries”) or by trucks to collection points, often situated in grocery stores. An alternative last-mile delivery solution is to deliver parcels to lockers where customers can pick them up. “Home deliveries” are known to be an expensive part of the supply chain, and cost and service efficiency vary with (uncertainty about) customers being present at home. Stores have their opening times, while parcel lockers can provide 24/7 access and also have higher potential to achieve a more economic and environmental sustainable solution, compared to home deliveries. This paper evaluates the cost and emissions implications of alternative solutions for last-mile delivery. A case study proposes and analyzes alternative expansion plans for a parcel locker distribution network in Norway. Results indicate that using parcel lockers is beneficial and the usage of more parcel locker delivery can improve service efficiency in last-mile delivery as it creates both the economic and environmental savings compared to home deliveries. An extended parcel locker network seems to be able to provide the optimal future delivery model that can operate more cost-efficiently and more sustainably than the delivery model under the current situation.

The impact of policy response to Covid-19 on the transportation and storage sector in Visegrad Countries (V4)

The paper is devoted to analysing national policy responses to the economic consequences of the COVID-19 pandemic in the Visegrad countries (Czechia, Hungary, Poland, and Slovakia) - on both the macroeconomic and microeconomic level. Focus is given to the transportation and storage sector (NACE Rev. 2 code H). The pandemic unevenly impacted this sector: while specific subsectors were thriving during this period (e.g. parcel delivery services), others were suffering due to abrupt mobility changes (e.g. public &amp; individual mobility services). Public policies were presented not only as a tool to reduce the negative impact of the pandemic but also to provide a platform to build new competitive advantages for national business entities, thus providing the rationale for an analysis of the actual impact of programs aimed at the transportation and storage sector. The impact of the state-aid focusing on the analysed was uneven between the analysed countries. Even though, the deployed programs have helped the industry to return to pre-pandemic levels within 4 quarters. This proves that apart from the structure of state-aid programs and schemes, an important factor was the pre-pandemic value chains. This could serve as a starting point for further research as more data become available.

Last-Mile Delivery Methods in E-Commerce: Does Perceived Sustainability Matter for Consumer Acceptance and Usage?

Sustainability has gained significant importance in e-commerce, as it impacts both consumer behavior and company success. This paper contributes to the literature on sustainability in e-commerce by studying the perceived sustainability of three common last-mile delivery methods (home delivery, parcel lockers, and click and collect) and other drivers of consumers’ acceptance of each delivery method (perceived costs, convenience). Based on a review of the relevant literature, a conceptual model integrating key determinants of consumers’ attitudes to delivery methods and their intention to use them is derived and tested using a sample of 536 German online buyers. The results demonstrate that perceived ease of use and perceived usefulness increase the acceptance of the delivery methods, whereas perceived costs constrain it. The findings reveal significant influences of perceived sustainability on the acceptance of the delivery methods, which vary between its three components (environmental, economic, and social) and regarding the delivery method. Retailers and collaborating parcel delivery services are advised to continue making last-mile delivery methods more convenient. However, they are also advised to implement standards in terms of environmental and social sustainability and inform customers about their efforts regarding sustainable last-mile delivery to build a competitive advantage in omni-channel retailing.

A Simulation Study of Risk-Aware Path Planning in Mitigating the Third-Party Risk of a Commercial UAS Operation in an Urban Area

UAS-based commercial services such as urban parcel delivery are expected to grow in the upcoming years and may lead to a large volume of UAS operations in urban areas. These flights may pose safety risks to persons and property on the ground, which are referred to as third-party risks. Path-planning methods have been developed to generate a nominal flight path for each UAS flight that poses relative low third-party risks by passing over less risky areas, e.g., areas with low-density unsheltered populations. However, it is not clear if risk minimization per flight works well in a commercial UAS operation that involves a large number of annual flights in an urban area. Recently, it has been shown that when using shortest flight path planning, a UAS-based parcel delivery service in an urban area can lead to society-critical third-party risk levels. The aim of this paper is to evaluate the mitigating effect of state-of-the-art risk-aware path planning on these society-critical third-party risk levels. To accomplish this, a third-party risk simulation using the shortest paths is extended with a state-of-the-art risk-aware path-planning method, and the societal effects on third-party risk levels have been assessed and compared to those obtained using shortest paths. The results show that state-of-the-art risk-aware path planning can reduce the total number of fatalities in an area, but at the cost of a critical increase in safety risks for persons living in areas that are favored by a state-of-the-art risk-aware path-planning method.

Autonomous Vehicle Intelligent System: Joint Ride-Sharing and Parcel Delivery Strategy

Autonomous vehicle (AV) integration poses a significant challenge for intelligent transportation systems (ITSs). The ability to automatically coordinate complex AV operations at scale is crucial for advancing the quality of core transportation services, such as ride-sharing and parcel delivery. However, existing studies have only considered either of these two services independently from the other, disregarding the potential benefits of their combined optimization. To address this open problem, we design an autonomous vehicle intelligent system (AVIS) providing joint ride-sharing and parcel delivery services under realistic ride and route constraints. We formulate the joint optimization problem through the scope of mixed-integer linear programming and solve it using the Lagrangian dual decomposition method to ensure scalability. We conduct extensive case studies to evaluate the performance of the proposed AVIS and its constituting components. Our experimental results demonstrate that AVIS can effectively provide both ride-sharing and parcel delivery services while satisfying service requests in transportation networks of various scales. In addition, the distributed method is shown to generate near-optimal solutions in reduced computation time.

Corrigendum to “Comparison of energy demands of drone-based and ground-based parcel delivery services” [Transp. Res. Part D: Transp. Environ. 78 (2020) 102209

Corrigendum to “Comparison of energy demands of drone-based and ground-based parcel delivery services” [Transp. Res. Part D: Transp. Environ. 78 (2020) 102209

An Estimated-Travel-Time Data Scraping and Analysis Framework for Time-Dependent Route Planning

Generally, a courier company needs to employ a fleet of vehicles to travel through a number of locations in order to provide efficient parcel delivery services. The route planning of these vehicles can be formulated as a vehicle routing problem (VRP). Most existing VRP algorithms assume that the traveling durations between locations are time invariant; thus, they normally use only a set of estimated travel times (ETTs) to plan the vehicles’ routes; however, this is not realistic because the traffic pattern in a city varies over time. One solution to tackle the problem is to use different sets of ETTs for route planning in different time periods, and these data are collectively called the time-dependent estimated travel times (TD-ETTs). This paper focuses on a low-cost and robust solution to effectively scrape, process, clean, and analyze the TD-ETT data from free web-mapping services in order to gain the knowledge of the traffic pattern in a city in different time periods. To achieve the abovementioned goal, our proposed framework contains four phases, namely, (i) Full Data Scraping, (ii) Data Pre-Processing and Analysis, (iii) Fast Data Scraping, and (iv) Data Patching and Maintenance. In our experiment, we used the above framework to obtain the TD-ETT data across 68 locations in Penang, Malaysia, for six months. We then fed the data to a VRP algorithm for evaluation. We found that the performance of our low-cost approach is comparable with that of using the expensive paid data.

Methodology for Prioritizing Best Practices Applied to the Sustainable Last Mile—The Case of a Brazilian Parcel Delivery Service Company

The ever-increasing impacts of the last mile delivery sector on the environment and the quality of life of the urban population, such as increased congestion, demand best practices to be incorporated by companies to reduce impacts such as emission of air pollutants and Greenhouse Gases (GHG) and depletion of natural resources, among others. However, a myriad of strategies has been developed for this purpose but there is a lack of methodologies that allow the choice of the best ones for a specific case. Therefore, this study looks for those best practices to be employed through an innovative methodology that consists of SWOT analysis (Strengths, Weaknesses, Opportunities, and Threats), a map of strategies of the delivery service, and using the Sustainability Balanced Scorecard (SBSC) and the Analytic Hierarchy Process (AHP), with the differential of considering the peculiarities of each company. The results applied in a Brazilian last mile delivery service company show that best practices such as route optimization, implementation of new infrastructure and business models for urban deliveries, and use of information systems for fleet tracking and monitoring contribute significantly to improving performance indicators and achieving the sector’s goal to become more sustainable, and especially meeting the Sustainable Development Goals (SDGs) 8, 9, 11, and 17.

From captive to captivating: The new customer journey model for companies

From purely transactional to personalised and unique, customer experiences can extend far beyond the exchange of goods. Companies often focus on functional and transactional experiences because they are the easiest to understand. A large part of purchase behaviour is, however, subjective and occurs in the context of the emotional relationship between companies and their customers. Together, Wharton Customer Analytics (WCA) and C Space explored and quantified the strength of this customer–company relationship while identifying the commercial benefits of customer-centricity (Customer Experience Code). Using the simple clustering method, k-means, WCA led the process of identifying discrete levels of customer-centricity and C Space augmented the analysis with new data on 160 companies. Together, WCA and C Space observed a significant relationship between the measure of a company’s customer-centricity and its performance. In addition, this study proposed a novel company journey framework, in which companies evolve from having a highly transactional customer relationship to one that is emotionally relevant and, crucially, provides the levers for improving customer-centricity. The framework also links this journey to the more typical customer satisfaction metric, net promoter score (NPS), and other measures of word-of-mouth (eg earned advocacy score [EAS]). A recent illustration of this journey is the surprising transformation of the logistics industry, which saw a large gain in emotional connections between 2019 and 2020. UPS, specifically, positively traversed all emotional categories and grew from the bottom to the top in less than a year. The data reveals that UPS’s response to the COVID-19 pandemic illustrated to their customers they are much more than a parcel delivery service.